10.1.10 Matching Issues for Stereo

Sanger, T.D.,
Stereo disparity computation using gabor Filters,
BioCyber(59), 1988, pp. 405-418. BibRef 8800

Hua, Z.D., Dubuisson, B.,
String Matching for Stereo Vision,
PRL(9), 1989, pp. 117-126. BibRef 8900

Wang, Y.P., and Pavlidis, T.,
Optimal Correspondence for String Subsequences,
PAMI(12), No. 11, November 1990, pp. 1080-1087.
IEEE Abstract.
IEEE DOI Application, Barcodes. Epi-polar line matching technique derived from string matching. BibRef 9011

Kim, D.H., Choi, W.Y., Park, R.H.,
Stereo Matching Technique Based on the Theory of Possibility,
PRL(13), 1992, pp. 735-744. BibRef 9200

Cochran, S.D.[Steven Douglas],
Adaptive Vergence for the Stereo Matching of Oblique Imagery,
PandRS(50), No. 4, August 1995, pp. 21-28. BibRef 9508
Earlier: ARPA94(II:1335-1348). BibRef
And: CMU-CS-TR-94-202, October 1994.
HTML Version. BibRef

Chan, K.L.[Kap-Luk],
Machine vision stereo matching,
US_Patent5,432,712, Jul 11, 1995
WWW Link. Matches along lines. BibRef 9507

Smith, P.W., Nandhakumar, N.,
An Improved Power Cepstrum Based Stereo Correspondence Method for Textured Scenes,
PAMI(18), No. 3, March 1996, pp. 338-348.
IEEE Abstract.
IEEE DOI BibRef 9603
Earlier:
An Accurate Stereo Correspondence Method for Textured Scenes Using Improved Power Cepstrum Techniques,
CVPR93(651-652).
IEEE DOI BibRef

Chiu, J.M.[Jui-Man], Chen, Z.[Zen], Chuang, J.H.[Jen-Hui], Chia, T.L.[Tsorng-Lin],
Determination of Feature Correspondences in Stereo Images Using a Calibration Polygon,
PR(30), No. 9, September 1997, pp. 1387-1400.
Elsevier DOI 9708
BibRef

Cai, L.D.[Li-Dong], Mayhew, J.E.W.[John E.W.],
A Note on Some Phase Differencing Algorithms for Disparity Estimation,
IJCV(22), No. 2, March 1997, pp. 111-124.
DOI Link 9706
BibRef

Cai, L.D.[Li-Dong], Mayhew, J.E.W.[John E.W.],
Estimating Mean Disparity of Stereo Images Using Shift-trials of Phase Differences,
BMVC92(xx-yy).
PDF File. 9209
BibRef

Torr, P.H.S., Davidson, C.,
IMPSAC: Synthesis of Importance Sampling and Random Sample Consensus,
PAMI(25), No. 3, March 2003, pp. 354-364.
IEEE DOI 0301
BibRef
Earlier: ECCV00(II: 819-833).
Springer DOI 0003
RANSAC. Recovery of epipolar geometry and correspondence with significant deformation (large baseline or rotation).
See also Structure from Motion without Correspondence.
See also Global Matching Framework for Stereo Computation, A. BibRef

Gutiérrez, S.[Salvador], Marroquín, J.L.[José Luis],
Robust approach for disparity estimation in stereo vision,
IVC(22), No. 3, 1 March 2004, pp. 183-195.
Elsevier DOI 0402
Use Gauss-Markov model to aid in matching. BibRef

Chum, O.[Ondrej], Pajdla, T.[Tomas], Sturm, P.F.[Peter F.],
The geometric error for homographies,
CVIU(97), No. 1, January 2005, pp. 86-102.
Elsevier DOI 0412
Find optimal point matches, for stereo and 3-D reconstruction. BibRef

Zhu, Q.[Qing], Zhao, J.[Jie], Lin, H.[Hui], Gong, J.Y.[Jian-Ya],
Triangulation of Well-Defined Points as a Constraint for Reliable Image Matching,
PhEngRS(71), No. 9, September 2005, pp. 1063-1070.
WWW Link. 0602
The reliability and accuracy of stereo image matching are improved by making use of the triangulation of well-defined points as a constraint. BibRef

Li, W.C.[Wan-Chiu], Leung, C.H., Hung, Y.S.,
Matching of uncalibrated stereo images by elastic deformation,
IJIST(14), No. 5, 2004, pp. 198-205.
DOI Link 0412
BibRef

Cheng, L.[Li], Caelli, T.M.[Terry M.],
Bayesian Stereo Matching,
CVIU(106), No. 1, April 2007, pp. 85-96.
Elsevier DOI 0704
BibRef
Earlier: GenModel04(192).
IEEE DOI 0406
Generative model; Stereo vision; Monte Carlo sampling; Bayesian analysis; Markov random field BibRef

Tang, J.[Jun], Liang, D.[Dong], Wang, N.[Nian], Fan, Y.Z.[Yi Zheng],
A Laplacian spectral method for stereo correspondence,
PRL(28), No. 12, 1 September 2007, pp. 1391-1399.
Elsevier DOI 0707
Correspondence; Laplacian spectrum; Doubly stochastic matrix; Thin plate spline (TPS) BibRef

Su, J.B.[Jian-Bo], Chung, R.[Ronald], Jin, L.[Liang],
Homography-based partitioning of curved surface for stereo correspondence establishment,
PRL(28), No. 12, 1 September 2007, pp. 1459-1471.
Elsevier DOI 0707
Stereo vision; Curved scene; Feature correspondence; Planar homography; Error analysis BibRef

Radhika, V.N., Kartikeyan, B., Krishna, B.G., Chowdhury, S., Srivastava, P.K.,
Robust Stereo Image Matching for Spaceborne Imagery,
GeoRS(45), No. 9, September 2007, pp. 2993-3000.
IEEE DOI 0710
BibRef

Hirschmuller, H.[Heiko],
Stereo Processing by Semiglobal Matching and Mutual Information,
PAMI(30), No. 2, February 2008, pp. 328-341.
IEEE DOI 0712
BibRef
Earlier:
Stereo Vision in Structured Environments by Consistent Semi-Global Matching,
CVPR06(II: 2386-2393).
IEEE DOI 0606
BibRef
Earlier:
Accurate and Efficient Stereo Processing by Semi-Global Matching and Mutual Information,
CVPR05(II: 807-814).
IEEE DOI 0507
BibRef

Ernst, I.[Ines], Hirschmüller, H.[Heiko],
Mutual Information Based Semi-Global Stereo Matching on the GPU,
ISVC08(I: 228-239).
Springer DOI 0812
BibRef

Zhu, Q.[Qing], Wu, B.[Bo], Tian, Y.X.[Yi-Xiang],
Propagation strategies for stereo image matching based on the dynamic triangle constraint,
PandRS(62), No. 4, September 2007, pp. 295-308.
Elsevier DOI 0711
Matching propagation; Dynamic triangle constraint; Stochastic propagation; Adjacent propagation; Self-adaptive propagation BibRef

Liang, B.D.[Bo-Dong], Chung, R.[Ronald],
Viewpoint Determination of Image by Interpolation over Sparse Samples,
IVC(26), No. 7, 2 July 2008, pp. 941-954.
Elsevier DOI 0804
BibRef
Earlier: ACCV06(I:399-408).
Springer DOI 0601
BibRef
And:
Stereo Matching by Interpolation,
ACCV06(I:439-448).
Springer DOI 0601
Function interpolation; Viewpoint determination BibRef

Gu, Z.[Zheng], Su, X.Y.[Xian-Yu], Liu, Y.K.[Yuan-Kun], Zhang, Q.C.[Qi-Can],
Local stereo matching with adaptive support-weight, rank transform and disparity calibration,
PRL(29), No. 9, 1 July 2008, pp. 1230-1235.
Elsevier DOI 0711
Stereo matching; Window-based; Disparity calibration BibRef

Son, T.T.[Tran Thai], Mita, S.[Seiichi],
Stereo Matching Algorithm Using a Simplified Trellis Diagram Iteratively and Bi-Directionally,
IEICE(E89-D), No. 1, January 2006, pp. 314-325.
DOI Link 0601
BibRef

Yoon, K.J.[Kuk-Jin], Kweon, I.S.[In So],
Distinctive Similarity Measure for stereo matching under point ambiguity,
CVIU(112), No. 2, November 2008, pp. 173-183.
Elsevier DOI 0811
BibRef
Earlier:
Stereo Matching with the Distinctive Similarity Measure,
ICCV07(1-7).
IEEE DOI 0710
BibRef
Earlier:
Stereo Matching with Symmetric Cost Functions,
CVPR06(II: 2371-2377).
IEEE DOI 0606
Stereo vision For Code:
See also Bilaterally Weighted Patches for Disparity Map Computation. For a variation:
See also Real-Time Spatiotemporal Stereo Matching Using the Dual-Cross-Bilateral Grid. BibRef

Yoon, K.J.,
Stereo matching based on nonlinear diffusion with disparity-dependent support weights,
IET-CV(6), No. 4, 2012, pp. 306-313.
DOI Link 1209
BibRef

Yoon, K.J.[Kuk-Jin], Jeong, Y.[Yekeun], Kweon, I.S.[In So],
Support Aggregation via Non-linear Diffusion with Disparity-Dependent Support-Weights for Stereo Matching,
ACCV09(I: 25-36).
Springer DOI 0909
BibRef

Park, M.G.[Min-Gyu], Yoon, K.J.[Kuk-Jin],
As-planar-as-possible depth map estimation,
CVIU(181), 2019, pp. 50-59.
Elsevier DOI 1903
Stereo matching, Plane estimation, Depth map refinement BibRef

Xiong, W.[Wei], Chung, H.S.[Hin Shun], Jia, J.Y.[Jia-Ya],
Fractional Stereo Matching Using Expectation-Maximization,
PAMI(31), No. 3, March 2009, pp. 428-443.
IEEE DOI 0902
Foreground object boundary blends with background. Color is not sufficient. Fractional is fraction of area in area match. BibRef

Nomura, A.[Atsushi], Ichikawa, M.[Makoto], Miike, H.[Hidetoshi],
Reaction-diffusion algorithm for stereo disparity detection,
MVA(20), No. 3, April 2009, pp. xx-yy.
Springer DOI 0903
BibRef
Earlier:
Stereo Vision System with the Grouping Process of Multiple Reaction-Diffusion Models,
IbPRIA05(I:137).
Springer DOI 0509
BibRef

Nomura, A.[Atsushi], Ichikawa, M.[Makoto], Okada, K.[Koichi], Miike, H.[Hidetoshi],
Long-Range Inhibition in Reaction-Diffusion Algorithms Designed for Edge Detection and Stereo Disparity Detection,
ACIVS10(I: 185-196).
Springer DOI 1012
BibRef

Agarwal, A.[Ankur], Blake, A.[Andrew],
Dense Stereo Matching over the Panum Band,
PAMI(32), No. 3, March 2010, pp. 416-430.
IEEE DOI 1002
BibRef
Earlier:
The Panum Proxy Algorithm for Dense Stereo Matching over a Volume of Interest,
CVPR06(II: 2339-2346).
IEEE DOI 0606
Panum Band: human stereo works over a narrow band of disparities. Using narrower range of disparities improves computation times. BibRef

Coffman, T.R.[Thayne R.], Bovik, A.C.[Alan C.],
Efficient Stereoscopic Ranging via Stochastic Sampling of Match Quality,
IP(19), No. 2, February 2010, pp. 451-460.
IEEE DOI 1002
BibRef
And:
Multi-view stereo ranging via Distributed Ray Tracing,
Southwest10(161-164).
IEEE DOI 1005
BibRef

Min, D.B.[Dong-Bo], Sohn, K.H.[Kwang-Hoon],
An asymmetric post-processing for correspondence problem,
SP:IC(25), No. 2, February 2010, pp. 130-142.
Elsevier DOI 1003
Adaptive filtering; Asymmetric consistency check; Post-processing; Stereo matching BibRef

Min, D.B.[Dong-Bo], Oh, J.[Juhyun], Sohn, K.H.[Kwang-Hoon],
Asymmetric post-processing for stereo correspondence,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Barrois, B.[Bjorn], Konrad, M.[Marcus], Wohler, C.[Christian], Gross, H.M.[Horst-Michael],
Resolving stereo matching errors due to repetitive structures using model information,
PRL(31), No. 12, 1 September 2010, pp. 1683-1692.
Elsevier DOI 1008
Stereo vision; Correspondence analysis; Model-based 3D scene analysis BibRef

Aydin, T.[Tarkan], Akgul, Y.S.[Yusuf Sinan],
Stereo depth estimation using synchronous optimization with segment based regularization,
PRL(31), No. 15, 1 November 2010, pp. 2389-2396.
Elsevier DOI 1003
BibRef
Earlier:
A Stereo Depth Recovery Method Using Layered Representation of the Scene,
DAGM09(322-331).
Springer DOI 0909
BibRef
Earlier:
3D Structure Recovery From Stereo Using Synchronous Optimization Processes,
BMVC06(III:1179).
PDF File. 0609
Stereo; Optimization; Segment based regularization; Anisotropic smoothing BibRef

Vural, U.[Ulas], Akgul, Y.S.[Yusuf Sinan],
A Multiple Graph Cut Based Approach for Stereo Analysis,
DAGM06(677-687).
Springer DOI 0610
BibRef

Donate, A.[Arturo], Liu, X.W.[Xiu-Wen], Collins, E.G.[Emmanuel G.],
Efficient Path-Based Stereo Matching With Subpixel Accuracy,
SMC-B(41), No. 1, February 2011, pp. 183-195.
IEEE DOI 1102
BibRef

Donate, A.[Arturo], Wang, Y.[Ying], Liu, X.W.[Xiu-Wen], Collins, E.G.[Emmanuel G.],
Efficient and accurate subpixel path based stereo matching,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Sabater, N.[Neus], Almansa, A.[Andrés], Morel, J.M.[Jean-Michel],
Meaningful Matches in Stereovision,
PAMI(34), No. 5, May 2012, pp. 930-942.
IEEE DOI 1204
Decide whether 2 blocks match reliably based on statistics of the image itself. Cannot rule out periodic structures. BibRef

Sabater, N.[Neus], Morel, J.M.[Jean-Michel], Almansa, A.[Andrés],
How Accurate Can Block Matches Be In Stereo Vision?,
SIIMS(4), No. 1, 2011, pp. 472-500.
DOI Link 1106
block-matching; subpixel accuracy; noise error estimate BibRef

Sabater, N.[Neus], Seifi, M.[Mozhdeh], Drazic, V.[Valter], Sandri, G.[Gustavo], Pérez, P.[Patrick],
Accurate Disparity Estimation for Plenoptic Images,
LightField14(548-560).
Springer DOI 1504
BibRef

Ghazouani, H.[Haythem], Tagina, M.[Moncef], Zapata, R.[René],
Fast and robust semi-local stereo matching using possibility distributions,
IJCVR(2), No. 3, 2011, pp. 237-253.
DOI Link 1110
BibRef

Neilson, D.[Daniel], Yang, Y.H.[Yee-Hong],
A Component-Wise Analysis of Constructible Match Cost Functions for Global Stereopsis,
PAMI(33), No. 11, November 2011, pp. 2147-2159.
IEEE DOI 1110
BibRef
Earlier:
Evaluation of constructable match cost measures for stereo correspondence using cluster ranking,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Zhang, K.[Ke], Lafruit, G.[Gauthier], Lauwereins, R.[Rudy], Van Gool, L.J.[Luc J.],
Constant Time Joint Bilateral Filtering Using Joint Integral Histograms,
IP(21), No. 9, September 2012, pp. 4309-4314.
IEEE DOI 1208
BibRef
Earlier:
Joint integral histograms and its application in stereo matching,
ICIP10(817-820).
IEEE DOI 1009
BibRef

Bethmann, F.[Folkmar], Luhmann, T.[Thomas],
Least-squares Matching with Advanced Geometric Transformation Models,
PFG(2011), No. 2, 2011, pp. 57-69.
WWW Link. 1211
BibRef
Earlier: CloseRange10(xx-yy).
PDF File. 1006
BibRef

Bethmann, F.[Folkmar], Luhmann, T.[Thomas],
Semi-Global Matching in Object Space,
PIA15(23-30).
DOI Link 1504
BibRef
Earlier:
Object-based Multi-Image Semi-Global Matching: Concept and first results,
CloseRange14(93-100).
DOI Link 1411
BibRef

Jepping, C., Bethmann, F.[Folkmar], Luhmann, T.[Thomas],
Congruence analysis of point clouds from unstable stereo image sequences,
CloseRange14(301-306).
DOI Link 1411
BibRef

Hosni, A.[Asmaa], Rhemann, C.[Christoph], Bleyer, M.[Michael], Rother, C.[Carsten], Gelautz, M.[Margrit],
Fast Cost-Volume Filtering for Visual Correspondence and Beyond,
PAMI(35), No. 2, February 2013, pp. 504-511.
IEEE DOI 1301
BibRef
Earlier: A2, A1, A3, A4, A5: CVPR11(3017-3024).
IEEE DOI 1106
Code, Stereo Matching. Matlab Code:
WWW Link. Code:
See also Stereo Disparity through Cost Aggregation with Guided Filter. BibRef

Hosni, A.[Asmaa], Bleyer, M.[Michael], Gelautz, M.[Margrit],
Secrets of adaptive support weight techniques for local stereo matching,
CVIU(117), No. 6, June 2013, pp. 620-632.
Elsevier DOI 1304
BibRef
Earlier: A1, A3, A2:
Accuracy-efficiency Evaluation of Adaptive Support Weight Techniques for Local Stereo Matching,
DAGM12(337-346).
Springer DOI 1209
Local stereo matching; Adaptive support weights; Evaluation study
See also Near Real-Time Stereo With Adaptive Support Weight Approaches. BibRef

Hosni, A.[Asmaa], Bleyer, M.[Michael], Gelautz, M.[Margrit],
Near Real-Time Stereo With Adaptive Support Weight Approaches,
3DPVT10(xx-yy).
PDF File. 1005

See also Accuracy-efficiency Evaluation of Adaptive Support Weight Techniques for Local Stereo Matching. BibRef

Hosni, A.[Asmaa], Bleyer, M.[Michael], Gelautz, M.[Margrit], Rhemann, C.[Christoph],
Local stereo matching using geodesic support weights,
ICIP09(2093-2096).
IEEE DOI 0911
BibRef

Da, F.P.[Fei-Peng], He, F.[Fu], Chen, Z.W.[Zhang-Wen],
Stereo Matching Based on Dissimilar Intensity Support and Belief Propagation,
JMIV(47), No. 1-2, September 2013, pp. 27-34.
WWW Link. 1307
BibRef
Earlier: A2, A1, Only:
Belief propagation with local edge detection-based cost aggregation for stereo matching,
ICIP11(2373-2376).
IEEE DOI 1201
BibRef

Pham, C.C.[Cuong Cao], Jeon, J.W.[Jae Wook],
Domain Transformation-Based Efficient Cost Aggregation for Local Stereo Matching,
CirSysVideo(23), No. 7, 2013, pp. 1119-1130.
IEEE DOI 1307
computational complexity BibRef

Lee, Z.C.[Zu-Cheul], Juang, J., Nguyen, T.Q.,
Local Disparity Estimation With Three-Moded Cross Census and Advanced Support Weight,
MultMed(15), No. 8, December 2013, pp. 1855-1864.
IEEE DOI 1402
computational complexity BibRef

Lee, Z.C.[Zu-Cheul], Nguyen, T.Q.,
Multi-Array Camera Disparity Enhancement,
MultMed(16), No. 8, December 2014, pp. 2168-2177.
IEEE DOI 1502
cameras BibRef

Yang, M.L.[Meng-Long], Liu, Y.G.[Yi-Guang], You, Z.S.[Zhi-Sheng], Li, X.F.[Xiao-Feng], Zhang, Y.[Yi],
A homography transform based higher-order MRF model for stereo matching,
PRL(40), No. 1, 2014, pp. 66-71.
Elsevier DOI 1403
Stereo matching BibRef

Nguyen, V.D.[Vinh Dinh], Nguyen, D.D.[Dung Duc], Nguyen, T.T.[Thuy Tuong], Dinh, V.Q.[Vinh Quang], Jeon, J.W.[Jae Wook],
Support Local Pattern and its Application to Disparity Improvement and Texture Classification,
CirSysVideo(24), No. 2, February 2014, pp. 263-276.
IEEE DOI 1403
Gaussian noise BibRef

Jain, A.K., Nguyen, T.Q.,
Discriminability Limits in Spatio-Temporal Stereo Block Matching,
IP(23), No. 5, May 2014, pp. 2328-2342.
IEEE DOI 1405
Cameras BibRef

Tan, P.[Pauline], Monasse, P.[Pascal],
Stereo Disparity through Cost Aggregation with Guided Filter,
IPOL(2014), No. 2014, pp. 252-275.
DOI Link 1411
Code, Stereo Matching.
See also Fast Cost-Volume Filtering for Visual Correspondence and Beyond. BibRef

Tan, X.[Xiao], Sun, C.M.[Chang-Ming], Sirault, X.[Xavier], Furbank, R.[Robert], Pham, T.D.[Tuan D.],
Stereo matching using cost volume watershed and region merging,
SP:IC(29), No. 10, 2014, pp. 1232-1244.
Elsevier DOI 1411
BibRef
Earlier:
Cross Image Inference Scheme for Stereo Matching,
ACCV12(IV:217-230).
Springer DOI 1304
3D/stereo scene analysis BibRef

Tan, X.[Xiao], Sun, C.M.[Chang-Ming], Pham, T.D.[Tuan D.],
Stereo matching based on multi-direction polynomial model,
SP:IC(44), No. 1, 2016, pp. 44-56.
Elsevier DOI 1605
Stereo matching BibRef

Tan, X.[Xiao], Sun, C.M.[Chang-Ming], Sirault, X.[Xavier], Furbank, R.[Robert], Pham, T.D.[Tuan D.],
Feature matching in stereo images encouraging uniform spatial distribution,
PR(48), No. 8, 2015, pp. 2530-2542.
Elsevier DOI 1505
3D/stereo scene analysis BibRef

Nguyen, V.D.[Vinh Dinh], Nguyen, D.D.[Duc Dung], Lee, S.J.[Sang Jun], Jeon, J.W.[Jae Wook],
Local Density Encoding for Robust Stereo Matching,
CirSysVideo(24), No. 12, December 2014, pp. 2049-2062.
IEEE DOI 1412
image matching BibRef

Dinh, V.Q.[Vinh Quang], Nguyen, V.D.[Vinh Dinh], Jeon, J.W.[Jae Wook],
Robust Matching Cost Function for Stereo Correspondence Using Matching by Tone Mapping and Adaptive Orthogonal Integral Image,
IP(24), No. 12, December 2015, pp. 5416-5431.
IEEE DOI 1512
image matching BibRef

Nguyen, V.D.[Vinh Dinh], Nguyen, H.V., Jeon, J.W.[Jae Wook],
Robust Stereo Data Cost With a Learning Strategy,
ITS(18), No. 2, February 2017, pp. 248-258.
IEEE DOI 1702
Algorithm design and analysis BibRef

Dinh, V.Q.[Vinh Quang], Nguyen, V.D.[Vinh Dinh], Nguyen, H.V.[H. Van], Jeon, J.W.[Jae Wook],
Fuzzy Encoding Pattern for Stereo Matching Cost,
CirSysVideo(26), No. 7, July 2016, pp. 1215-1228.
IEEE DOI 1608
fuzzy set theory BibRef

Mozerov, M.G., van de Weijer, J.,
Accurate Stereo Matching by Two-Step Energy Minimization,
IP(24), No. 3, March 2015, pp. 1153-1163.
IEEE DOI 1502
Computational modeling BibRef

Mozerov, M.G., van de Weijer, J.,
Global Color Sparseness and a Local Statistics Prior for Fast Bilateral Filtering,
IP(24), No. 12, December 2015, pp. 5842-5853.
IEEE DOI 1512
approximation theory BibRef

Mozerov, M.G., van de Weijer, J.,
Improved Recursive Geodesic Distance Computation for Edge Preserving Filter,
IP(26), No. 8, August 2017, pp. 3696-3706.
IEEE DOI 1707
computational complexity, differential geometry, edge detection, graph theory, image denoising, image filtering, recursive filters, 1D recursions, O(8P) computational complexity, edge preserving filter, geodesic distance affinity, geodesic distance-based recursive filter, image denoising, image plane, improved recursive geodesic distance computation, maximum influence propagation method, orthogonal directions, Approximation algorithms, Computational complexity, Dynamic programming, Image edge detection, Kernel, Noise reduction, Geodesic distance filter, color image filtering, image, enhancement BibRef

Jiao, J.B.[Jian-Bo], Wang, R.G.[Rong-Gang], Wang, W.M.[Wen-Min], Dong, S.F.[Sheng-Fu], Wang, Z.Y.[Zhen-Yu], Gao, W.[Wen],
Local Stereo Matching with Improved Matching Cost and Disparity Refinement,
MultMedMag(21), No. 4, October 2014, pp. 16-27.
IEEE DOI 1502
filtering theory BibRef

Jiao, J.B.[Jian-Bo], Wang, R.G.[Rong-Gang], Wang, W.M.[Wen-Min], Li, D., Gao, W.[Wen],
Color Image-Guided Boundary-Inconsistent Region Refinement for Stereo Matching,
CirSysVideo(27), No. 5, May 2017, pp. 1155-1159.
IEEE DOI 1705
Color, Computers, Image edge detection, Image segmentation, Media, Optimization, Pipelines, Boundary, Kinect, disparity refinement, stereo, matching BibRef

Yaman, M.[Mustafa], Kalkan, S.[Sinan],
An iterative adaptive multi-modal stereo-vision method using mutual information,
JVCIR(26), No. 1, 2015, pp. 115-131.
Elsevier DOI 1502
Multi-modal stereo-vision BibRef

Zhang, K.[Ka], Sheng, Y.[Yehua], Lv, H.Y.[Hai-Yang],
Stereo matching cost computation based on nonsubsampled contourlet transform,
JVCIR(26), No. 1, 2015, pp. 275-283.
Elsevier DOI 1502
Stereo image matching BibRef

Yang, Q.,
Local Smoothness Enforced Cost Volume Regularization for Fast Stereo Correspondence,
SPLetters(22), No. 9, September 2015, pp. 1429-1433.
IEEE DOI 1503
Accuracy BibRef

Julià, L.F.[Laura Fernández], Monasse, P.[Pascal],
Bilaterally Weighted Patches for Disparity Map Computation,
IPOL(5), 2015, pp. 73-89.
DOI Link 1503
Code, Stereo Matching. Based on:
See also Distinctive Similarity Measure for stereo matching under point ambiguity.
See also Stereo Disparity through Cost Aggregation with Guided Filter. BibRef

Saygili, G.[Gorkem], van der Maaten, L.[Laurens], Hendriks, E.A.[Emile A.],
Adaptive stereo similarity fusion using confidence measures,
CVIU(135), No. 1, 2015, pp. 95-108.
Elsevier DOI 1504
BibRef
Earlier:
Stereo Similarity Metric Fusion Using Stereo Confidence,
ICPR14(2161-2166)
IEEE DOI 1412
Accuracy; Estimation; Fuses; Robustness; Stereo vision; Weight measurement Stereo confidence measures. BibRef

Lee, S.[Sehyung], Lee, J.H.[Jin Han], Lim, J.W.[Jong-Woo], Suh, I.H.[Il Hong],
Robust stereo matching using adaptive random walk with restart algorithm,
IVC(37), No. 1, 2015, pp. 1-11.
Elsevier DOI 1505
Global optimization BibRef

Liang, J.[Jun], Maybank, S.J.[Stephen J.], Zhang, Y.N.[Yan-Ning],
Stereo matching-based definition of saliency via sample-based Kullback-Leibler divergence estimation,
MVA(26), No. 5, July 2015, pp. 607-618.
WWW Link. 1506
BibRef

Liu, J.[Jing], Li, C.P.[Chun-Peng], Mei, F.[Feng], Wang, Z.Q.[Zhao-Qi],
3D entity-based stereo matching with ground control points and joint second-order smoothness prior,
VC(31), No. 9, September 2015, pp. 1253-1269.
Springer DOI 1508
BibRef

Huang, J.Z.[Jing-Zhou],
Stereo matching based on segmented B-spline surface fitting and accelerated region belief propagation,
IET-CV(9), No. 4, 2015, pp. 456-466.
DOI Link 1509
image matching BibRef

Malathi, T., Bhuyan, M.K.,
Estimation of disparity map of stereo image pairs using spatial domain local Gabor wavelet,
IET-CV(9), No. 4, 2015, pp. 595-602.
DOI Link 1509
Gabor filters BibRef

Pham, C.C.[Cuong Cao], Dinh, V.Q.[Vinh Quang], Jeon, J.W.[Jae Wook],
Robust non-local stereo matching for outdoor driving images using segment-simple-tree,
SP:IC(39, Part A), No. 1, 2015, pp. 173-184.
Elsevier DOI 1512
Stereo matching BibRef

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Backward compatible HDR stereo matching: A hybrid tone-mapping-based framework,
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A fast non-local disparity refinement method for stereo matching,
ICIP14(3823-3827)
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Accuracy BibRef

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Histogram-based cost aggregation strategy with joint bilateral filtering for stereo matching,
IET-CV(10), No. 3, 2016, pp. 173-181.
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filtering theory BibRef

Zhan, Y.L.[Yun-Long], Gu, Y.Z.[Yu-Zhang], Zhang, X.L.[Xiao-Lin], Qu, L.[Lei], Pi, J.T.[Jia-Tian], Huang, X.X.[Xiao-Xia], Wang, Y.G.[Ying-Guan], Luo, J.F.[Ju-Feng], Qiu, Y.Z.[Yun-Zhou],
Stereo Matching Based on Efficient Image-Guided Cost Aggregation,
IEICE(E99-D), No. 3, March 2016, pp. 781-784.
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Zhan, Y.L.[Yun-Long], Gu, Y.Z.[Yu-Zhang], Huang, K.[Kui], Zhang, C.[Cheng], Hu, K.[Keli],
Accurate Image-Guided Stereo Matching With Efficient Matching Cost and Disparity Refinement,
CirSysVideo(26), No. 9, September 2016, pp. 1632-1645.
IEEE DOI 1609
Accuracy BibRef

Song, K.C.[Ke-Chen], Wen, X.[Xin], Zhao, Y.J.[Yong-Jie], Dong, Z.P.[Zhi-Peng], Yan, Y.H.[Yun-Hui],
Noise robust image matching using adjacent evaluation census transform and wavelet edge joint bilateral filter in stereo vision,
JVCIR(38), No. 1, 2016, pp. 487-503.
Elsevier DOI 1605
Stereo matching BibRef

Spyropoulos, A.[Aristotle], Mordohai, P.[Philippos],
Correctness Prediction, Accuracy Improvement and Generalization of Stereo Matching Using Supervised Learning,
IJCV(118), No. 3, July 2016, pp. 300-318.
Springer DOI 1608
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Spyropoulos, A.[Aristotle], Komodakis, N.[Nikos], Mordohai, P.[Philippos],
Learning to Detect Ground Control Points for Improving the Accuracy of Stereo Matching,
CVPR14(1621-1628)
IEEE DOI 1409
3D Stereo correspondence BibRef

Liu, T., Peng, X., Qiao, L.,
Window-Based Three-Dimensional Aggregation for Stereo Matching,
SPLetters(23), No. 7, July 2016, pp. 1008-1012.
IEEE DOI 1608
Aggregates BibRef

Zhu, S.Q.[Shi-Qiang], Wang, Z.[Zhi], Zhang, X.Q.[Xue-Qun], Li, Y.H.[Yue-Hua],
Edge-preserving guided filtering based cost aggregation for stereo matching,
JVCIR(39), No. 1, 2016, pp. 107-119.
Elsevier DOI 1608
Stereo matching BibRef

Liu, M.[Mohan], Müller, K.[Karsten], Raake, A.[Alexander],
Efficient no-reference metric for sharpness mismatch artifact between stereoscopic views,
JVCIR(39), No. 1, 2016, pp. 132-141.
Elsevier DOI 1608
Sharpness mismatch BibRef

Choi, O.[Ouk], Chang, H.S.[Hyun Sung],
Yet Another Cost Aggregation Over Models,
IP(25), No. 11, November 2016, pp. 5397-5410.
IEEE DOI 1610
Adaptation models BibRef

Lin, C.[Chuan], Li, Y.[Ya], Xu, G.[Guili], Cao, Y.J.[Yi-Jun],
Optimizing ZNCC calculation in binocular stereo matching,
SP:IC(52), No. 1, 2017, pp. 64-73.
Elsevier DOI 1701
Stereo matching BibRef

Hamzah, R.A.[Rostam Affendi], Ibrahim, H.[Haidi], Hassan, A.H.A.[Anwar Hasni Abu],
Stereo matching algorithm based on per pixel difference adjustment, iterative guided filter and graph segmentation,
JVCIR(42), No. 1, 2017, pp. 145-160.
Elsevier DOI 1701
Iterative guided filter BibRef

Ma, H.[Hao], Zheng, S.Y.[Shun-Yi], Li, C.[Chang], Li, Y.S.[Ying-Song], Gui, L.[Li], Huang, R.Y.[Rong-Yong],
Cross-scale cost aggregation integrating intrascale smoothness constraint with weighted least squares in stereo matching,
JOSA-A(34), No. 4, April 2017, pp. 648-656.
DOI Link 1704
Digital image processing; Algorithms ; Robotic and machine control BibRef

Yin, J.H.[Ji-Hao], Zhu, H.M.[Hong-Mei], Yuan, D.[Ding], Xue, T.F.[Tian-Fan],
Sparse representation over discriminative dictionary for stereo matching,
PR(71), No. 1, 2017, pp. 278-289.
Elsevier DOI 1707
Computer, vision BibRef

Zhu, H.M.[Hong-Mei], Yin, J.H.[Ji-Hao], Yuan, D.[Ding],
SVCV: segmentation volume combined with cost volume for stereo matching,
IET-CV(11), No. 8, December 2017, pp. 733-743.
DOI Link 1712
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Zhu, H.M.[Hong-Mei], Yin, J.H.[Ji-Hao], Yuan, D.[Ding], Sui, W.[Wei],
Fluctuations of disparity space image for stereo matching in untextured regions,
ICIP15(1578-1582)
IEEE DOI 1512
Computer vision BibRef

Zhu, S.P.[Shi-Ping], Yan, L.[Lina],
Local stereo matching algorithm with efficient matching cost and adaptive guided image filter,
VC(33), No. 9, September 2017, pp. 1087-1102.
WWW Link. 1708
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Cheng, F.Y.[Fei-Yang], He, X.M.[Xu-Ming], Zhang, H.[Hong],
Learning to refine depth for robust stereo estimation,
PR(74), No. 1, 2018, pp. 122-133.
Elsevier DOI 1711
Stereo matching BibRef

Fei, L., Yan, L., Chen, C., Ye, Z., Zhou, J.,
OSSIM: An Object-Based Multiview Stereo Algorithm Using SSIM Index Matching Cost,
GeoRS(55), No. 12, December 2017, pp. 6937-6949.
IEEE DOI 1712
Image quality, Image reconstruction, Indexes, Optimization, Software, Software algorithms, structural similarity (SSIM) index BibRef

Lee, Y.M.[Yeong-Min], Park, M.G., Hwang, Y., Shin, Y., Kyung, C.M.[Chong-Min],
Memory-Efficient Parametric Semiglobal Matching,
SPLetters(25), No. 2, February 2018, pp. 194-198.
IEEE DOI 1802
Gaussian processes, image matching, stereo image processing, GMM parameters, Gaussian mixture model function, KITTI dataset, stereo matching BibRef

Gonzalez-Huitron, V.[Victor], Ponomaryov, V.[Volodymyr], Ramos-Diaz, E.[Eduardo], Sadovnychiy, S.[Sergiy],
Parallel framework for dense disparity map estimation using Hamming distance,
SIViP(12), No. 2, February 2018, pp. 231-238.
Springer DOI 1802
BibRef

Dong, H., Wang, T., Yu, X., Ren, P.,
Stereo Matching via Dual Fusion,
SPLetters(25), No. 5, May 2018, pp. 615-619.
IEEE DOI 1805
image fusion, image matching, stereo image processing, dual fusion, fused aggregated costs, guided filtered costs, stereo matching, stereo matching BibRef

Hamzah, R.A.[Rostam Affendi], Kadmin, A.F.[A. Fauzan], Hamid, M.S.[M. Saad], Ghani, S.F.A.[S. Fakhar A.], Ibrahim, H.[Haidi],
Improvement of stereo matching algorithm for 3D surface reconstruction,
SP:IC(65), 2018, pp. 165-172.
Elsevier DOI 1805
3D reconstruction, Adaptive support weight, Gradient matching, Guided filter, Stereo matching BibRef

Yao, P.[Peng], Zhang, H.[Hua], Xue, Y.B.[Yan-Bing], Chen, S.Y.[Sheng-Yong],
MSCS: MeshStereo with Cross-Scale Cost Filtering for fast stereo matching,
IET-CV(12), No. 6, September 2018, pp. 908-918.
DOI Link 1808
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Yao, P.[Peng], Feng, J.Q.[Jie-Qing],
Stacking learning with coalesced cost filtering for accurate stereo matching,
JVCIR(78), 2021, pp. 103169.
Elsevier DOI 2107
Stereo matching, Stacking, Random Forest, One-view disparity refinement BibRef

Yao, P.[Peng], Zhang, H.[Hua], Xue, Y.B.[Yan-Bing], Chen, S.Y.[Sheng-Yong],
As-global-as-possible stereo matching with adaptive smoothness prior,
IET-IPR(13), No. 1, January 2019, pp. 98-107.
DOI Link 1812
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Williem, W., Park, I.K.[In Kyu],
Deep self-guided cost aggregation for stereo matching,
PRL(112), 2018, pp. 168-175.
Elsevier DOI 1809
stereo matching, cost aggregation, deep learning, guided-filter BibRef

Taniai, T.[Tatsunori], Matsushita, Y.[Yasuyuki], Sato, Y.[Yoichi], Naemura, T.[Takeshi],
Continuous 3D Label Stereo Matching Using Local Expansion Moves,
PAMI(40), No. 11, November 2018, pp. 2725-2739.
IEEE DOI 1810
BibRef
Earlier: A1, A2, A4, Only:
Graph Cut Based Continuous Stereo Matching Using Locally Shared Labels,
CVPR14(1613-1620)
IEEE DOI 1409
Optimization, Proposals, Image segmentation, Acceleration, Pattern matching, Stereo vision, discrete-continuous optimization BibRef

Baráth, D.[Dániel],
Efficient energy-based topological outlier rejection,
CVIU(174), 2018, pp. 70-81.
Elsevier DOI 1812
Stereo vision, Outlier filtering, Energy minimization, Point correspondences BibRef

Lu, C.H.[Chuan-Hua], Uchiyama, H.[Hideaki], Thomas, D.[Diego], Shimada, A.[Atsushi], Taniguchi, R.I.[Rin-Ichiro],
Sparse Cost Volume for Efficient Stereo Matching,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812
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Dong, Q.C.[Qi-Cong], Feng, J.Q.[Jie-Qing],
Outlier detection and disparity refinement in stereo matching,
JVCIR(60), 2019, pp. 380-390.
Elsevier DOI 1903
Outlier detection, Stereo matching, Match fixed point jumps, Normal-based plane fitting BibRef

Cheng, H., Zhang, J., Wu, Q., An, P.,
A Computational Model for Stereoscopic Visual Saliency Prediction,
MultMed(21), No. 3, March 2019, pp. 678-689.
IEEE DOI 1903
feature extraction, image colour analysis, object detection, stereo image processing, multi-feature saliency prediction BibRef

Dudek, R.[Roman], Croci, S.[Simone], Smolic, A.[Aljosa], Knorr, S.[Sebastian],
Robust global and local color matching in stereoscopic omnidirectional content,
SP:IC(74), 2019, pp. 231-241.
Elsevier DOI 1904
Virtual reality, 360-video, Color matching, Binocular rivalry, Omnidirectional images, Stereoscopic 3D BibRef

Park, M.G.[Min-Gyu], Yoon, K.J.[Kuk-Jin],
Learning and Selecting Confidence Measures for Robust Stereo Matching,
PAMI(41), No. 6, June 2019, pp. 1397-1411.
IEEE DOI 1905
BibRef
Earlier:
Leveraging stereo matching with learning-based confidence measures,
CVPR15(101-109)
IEEE DOI 1510
Forestry, Robustness, Modulation, Prediction algorithms, Feature extraction, Training data, Computational modeling, feature selection BibRef

Mozerov, M.G., van de Weijer, J.,
One-View Occlusion Detection for Stereo Matching With a Fully Connected CRF Model,
IP(28), No. 6, June 2019, pp. 2936-2947.
IEEE DOI 1905
image matching, random processes, stereo image processing, trees (mathematics), OVOD solution, energy minimization process, geodesic distance filter BibRef

Li, C.H.[Chun-Hua], An, P.[Ping], Shen, L.Q.[Li-Quan], Li, K.[Kai],
A Modified Just Noticeable Depth Difference Model Built in Perceived Depth Space,
MultMed(21), No. 6, June 2019, pp. 1464-1475.
IEEE DOI 1906
Convergence, Solid modeling, Stereo image processing, Adaptation models, Retina, Physiology, binocular disparity BibRef

Kim, S.[Sijung], Jang, J.[Jinbeum], Lim, J.[Jaeseung], Paik, J.[Joonki], Lee, S.K.[Sang-Keun],
Disparity-selective stereo matching using correlation confidence measure,
JOSA-A(35), No. 9, September 2018, pp. 1653-1662.
DOI Link 1912
Digital image processing, Three-dimensional image processing, Vision - binocular and stereopsis, Feature extraction, Three dimensional reconstruction BibRef

Jiang, S.[San], Jiang, W.S.[Wan-Shou],
Efficient match pair selection for oblique UAV images based on adaptive vocabulary tree,
PandRS(161), 2020, pp. 61-75.
Elsevier DOI 2002
Unmanned aerial vehicle, Oblique photogrammetry, Image retrieval, Adaptive vocabulary tree, Structure from motion BibRef

He, S.[Sheng], Zhou, R.[Ruqin], Li, S.[Shenhong], Jiang, S.[San], Jiang, W.S.[Wan-Shou],
Disparity Estimation of High-Resolution Remote Sensing Images with Dual-Scale Matching Network,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
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Zhang, Z.[Zihao], Wang, Y.Q.[Yuan-Qing], Huang, T.[Ting], Zhan, L.[Lingli],
A weighting algorithm based on the gravitational model for local stereo matching,
SIViP(14), No. 2, March 2020, pp. 315-323.
WWW Link. 2003
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Zhu, C.T.[Cheng-Tao], Chang, Y.Z.[Yau-Zen],
Stereo matching for infrared images using guided filtering weighted by exponential moving average,
IET-IPR(14), No. 5, 17 April 2020, pp. 830-837.
DOI Link 2004
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Nguyen, P.H.[Phuc Hong], Ahn, C.W.[Chang Wook],
Parameter selection framework for stereo correspondence,
MVA(31), No. 4, April 2020, pp. Article27.
Springer DOI 2005
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Brandt, R.[Rafaël], Strisciuglio, N.[Nicola], Petkov, N.[Nicolai], Wilkinson, M.H.F.[Michael H.F.],
Efficient binocular stereo correspondence matching with 1-D Max-Trees,
PRL(135), 2020, pp. 402-408.
Elsevier DOI 2006
Stereo matching, Mathematical morphology, Tree structures BibRef

Ma, Z.J.[Zhong-Jian], Huang, D.Z.[Dong-Zhen], Li, B.Q.[Bao-Qing], Yuan, X.B.[Xiao-Bing],
Asymmetric Learning for Stereo Matching Cost Computation,
IEICE(E103-D), No. 10, October 2020, pp. 2162-2167.
WWW Link. 2010
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Zhang, H.[Hong], Li, H.J.[Hao-Jie], Wang, Z.H.[Zhi-Hui], Yue, Y.X.[Yu-Xin], Chen, S.L.[Sheng-Lun],
Geometry and context guided refinement for stereo matching,
IET-IPR(14), No. 12, October 2020, pp. 2652-2659.
DOI Link 2010
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Suresh, C.[Chitra], Tuckley, K.R.[Kushal R.],
Computing disparity map using minimum sum belief propagation for stereo pair images,
IJCVR(10), No. 5, 2020, pp. 489-504.
DOI Link 2011
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Lee, Y.M.[Yeong-Min], Kyung, C.M.[Chong-Min],
A Memory- and Accuracy-Aware Gaussian Parameter-Based Stereo Matching Using Confidence Measure,
PAMI(43), No. 6, June 2021, pp. 1845-1858.
IEEE DOI 2106
Memory management, Bandwidth, Filtering, Real-time systems, Random forests, Pattern matching, Gaussian mixture model, cost aggregation BibRef

Yuan, W.M.[Wei-Min], Meng, C.[Cai], Tong, X.Y.[Xiao-Yan], Li, Z.X.[Zhao-Xi],
Efficient local stereo matching algorithm based on fast gradient domain guided image filtering,
SP:IC(95), 2021, pp. 116280.
Elsevier DOI 2106
Stereo matching, Cost aggregation, Disparity refinement, Guided image filtering BibRef

Zhang, C.X.[Cong-Xuan], Wu, J.J.[Jun-Jie], Chen, Z.[Zhen], Liu, W.[Wen], Li, M.[Ming], Jiang, S.F.[Shao-Feng],
Dense-CNN: Dense convolutional neural network for stereo matching using multiscale feature connection,
SP:IC(95), 2021, pp. 116285.
Elsevier DOI 2106
Stereo matching, Cost volume, Multiscale features, Dense convolutional neural network BibRef

Yang, S.[Shan], Lei, X.Y.[Xin-Yue], Liu, Z.F.[Zhen-Feng], Sui, G.R.[Guo-Rong],
An efficient local stereo matching method based on an adaptive exponentially weighted moving average filter in SLIC space,
IET-IPR(15), No. 8, 2021, pp. 1722-1732.
DOI Link 2106
BibRef

Fu, Y.[Yuli], Lai, K.[Kaimin], Chen, W.X.[Wei-Xiang], Xiang, Y.[Youjun],
A pixel pair-based encoding pattern for stereo matching via an adaptively weighted cost,
IET-IPR(15), No. 4, 2021, pp. 908-917.
DOI Link 2106
BibRef

Jin, Y.S.[Yu-Sheng], Zhao, H.[Hong], Bu, P.H.[Peng-Hui],
Spatial-tree filter for cost aggregation in stereo matching,
IET-IPR(15), No. 10, 2021, pp. 2135-2145.
DOI Link 2108
BibRef

Ji, P.L.[Peng-Lei], Li, J.[Jie], Li, H.C.[Han-Chao], Liu, X.G.[Xin-Guo],
Superpixel alpha-expansion and normal adjustment for stereo matching,
JVCIR(79), 2021, pp. 103238.
Elsevier DOI 2109
Stereo matching, Superpixel, Alpha-expansion, Graph cuts, Normal adjustment BibRef

Wu, S.S.[Sih-Sian], Chen, H.H.[Hon-Hui], Chen, L.G.[Liang-Gee],
Hardware- and Memory-Efficient Architecture for Disparity Estimation of Large Label Counts,
CirSysVideo(31), No. 9, September 2021, pp. 3679-3693.
IEEE DOI 2109
Random access memory, Hardware, Buffer storage, Belief propagation, Memory management, Engines, System-on-chip, VLSI circuit design BibRef

Lai, Y.C.[Yen-Chieh], Cheng, C.C.[Chao-Chung], Liang, C.K.[Chia-Kai], Chen, L.G.[Liang-Gee],
Efficient message reduction algorithm for stereo matching using belief propagation,
ICIP10(2977-2980).
IEEE DOI 1009
BibRef

Wang, C.[Chen], Bai, X.[Xiao], Wang, X.[Xiang], Liu, X.L.[Xiang-Long], Zhou, J.[Jun], Wu, X.Y.[Xin-Yu], Li, H.D.[Hong-Dong], Tao, D.C.[Da-Cheng],
Self-Supervised Multiscale Adversarial Regression Network for Stereo Disparity Estimation,
Cyber(51), No. 10, October 2021, pp. 4770-4783.
IEEE DOI 2110
Estimation, Feature extraction, Training, Sensors, Generative adversarial networks, Generators, Annotations, stereo disparity estimation BibRef

Sun, S.Q.[Shu-Qiao], Liu, R.K.[Rong-Ke], Sun, S.T.[Shan-Tong],
DESA: Disparity Estimation With Surface Awareness,
SPLetters(28), 2021, pp. 2028-2032.
IEEE DOI 2111
Costs, Estimation, Training, Geometry, Sun, Distortion, Stereo matching, depth map, scene reconstruction, surface normal BibRef

Cheng, C.[Chunbo], Li, H.[Hong], Zhang, L.M.[Li-Ming],
Two-Branch Deconvolutional Network With Application in Stereo Matching,
IP(31), 2022, pp. 327-340.
IEEE DOI 2112
Image reconstruction, Feature extraction, Costs, Estimation, Convolutional neural networks, Convolution, disparity estimation network BibRef

Zeng, K.[Kai], Wang, Y.[Yaonan], Mao, J.[Jianxu], Liu, C.[Caiping], Peng, W.X.[Wei-Xing], Yang, Y.[Yin],
Deep Stereo Matching With Hysteresis Attention and Supervised Cost Volume Construction,
IP(31), 2022, pp. 812-822.
IEEE DOI 2201
Costs, Feature extraction, Hysteresis, Convolution, Correlation, Optimization, Stereo matching, unary feature maps, group convolution cost BibRef

Li, X.[Xing], Fan, Y.Y.[Yang-Yu], Rao, Z.B.[Zhi-Bo], Lv, G.Y.[Guo-Yun], Liu, S.[Shiya],
Synthetic-to-Real Domain Adaptation Joint Spatial Feature Transform for Stereo Matching,
SPLetters(29), 2022, pp. 60-64.
IEEE DOI 2202
Image edge detection, Generators, Transforms, Fuses, Training, Task analysis, Image reconstruction, Domain adaptation, edge cues BibRef

Song, X.[Xiao], Yang, G.[Guorun], Zhu, X.G.[Xin-Ge], Zhou, H.[Hui], Ma, Y.X.[Yue-Xin], Wang, Z.[Zhe], Shi, J.P.[Jian-Ping],
AdaStereo: An Efficient Domain-Adaptive Stereo Matching Approach,
IJCV(130), No. 2, February 2022, pp. 226-245.
Springer DOI 2202
BibRef
And: Correction: IJCV(130), No. 3, March 2022, pp. 884-884.
Springer DOI 2203
BibRef
Earlier: A1, A2, A3, A4, A6, A7, Only:
AdaStereo: A Simple and Efficient Approach for Adaptive Stereo Matching,
CVPR21(10323-10332)
IEEE DOI 2111
Adaptation models, Costs, Image color analysis, Computational modeling, Pipelines, Benchmark testing, Task analysis BibRef

Huang, C.H.[Chih-Hsuan], Yang, J.F.[Jar-Ferr],
Improved quadruple sparse census transform and adaptive multi-shape aggregation algorithms for precise stereo matching,
IET-CV(16), No. 2, 2022, pp. 159-179.
DOI Link 2202
adaptive support weight, census transform, cost aggregation, depth estimation, multi-shape aggregation, stereo matching BibRef

Wang, C.[Chen], Wang, X.[Xiang], Zhang, J.W.[Jia-Wei], Zhang, L.[Liang], Bai, X.[Xiao], Ning, X.[Xin], Zhou, J.[Jun], Hancock, E.[Edwin],
Uncertainty Estimation for Stereo Matching Based on Evidential Deep Learning,
PR(124), 2022, pp. 108498.
Elsevier DOI 2203
Stereo matching, Uncertainty estimation, Evidential deep learning BibRef

Cheng, X.J.[Xian-Jing], Zhao, Y.[Yong], Yang, W.B.[Wen-Bang], Hu, Z.J.[Zhi-Jun], Yu, X.M.[Xiao-Min], Zhao, H.L.[Hao-Liang], Zeng, P.C.[Peng-Cheng],
A novel cell structure-based disparity estimation for unsupervised stereo matching,
IET-IPR(16), No. 6, 2022, pp. 1678-1693.
DOI Link 2204
BibRef

Zhong, Y.R.[Yi-Ran], Loop, C.[Charles], Byeon, W.M.[Won-Min], Birchfield, S.T.[Stan T.], Dai, Y.C.[Yu-Chao], Zhang, K.H.[Kai-Hao], Kamenev, A.[Alexey], Breuel, T.[Thomas], Li, H.D.[Hong-Dong], Kautz, J.[Jan],
Displacement-Invariant Cost Computation for Stereo Matching,
IJCV(130), No. 5, May 2022, pp. 1196-1209.
Springer DOI 2205
BibRef

Zhang, C.H.[Cheng-Hao], Meng, G.F.[Gao-Feng], Su, B.[Bing], Xiang, S.M.[Shi-Ming], Pan, C.H.[Chun-Hong],
Monocular contextual constraint for stereo matching with adaptive weights assignment,
IVC(121), 2022, pp. 104424.
Elsevier DOI 2205
Deep learning, Stereo matching, Monocular contextual constraint, Adaptive weights assignment BibRef

Chen, W.[Wen], Chen, H.[Hao], Yang, S.[Shuting],
Self-Supervised Stereo Matching Method Based on SRWP and PCAM for Urban Satellite Images,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Li, X.[Xing], Fan, Y.[Yangyu], Rao, Z.B.[Zhi-Bo], Guo, Z.[Zhe], Lv, G.[Guoyun],
Improving Stereo Matching Generalization via Fourier-Based Amplitude Transform,
SPLetters(29), 2022, pp. 1362-1366.
IEEE DOI 2206
Fats, Image reconstruction, Training, Semantics, Fourier transforms, Costs, Testing, Stereo matching, Fourier-based amplitude transform, cross-domain generalization capability BibRef

Zhang, H.[Hong], Ye, X.C.[Xin-Chen], Chen, S.[Shenglun], Wang, Z.H.[Zhi-Hui], Li, H.J.[Hao-Jie], Ouyang, W.L.[Wan-Li],
The Farther the Better: Balanced Stereo Matching via Depth-Based Sampling and Adaptive Feature Refinement,
CirSysVideo(32), No. 7, July 2022, pp. 4613-4625.
IEEE DOI 2207
Feature extraction, Estimation, Costs, Image resolution, Pipelines, Task analysis, Depth estimation, stereo matching, automatic driving BibRef

Ye, X.Q.[Xiao-Qian], Yan, B.B.[Bin-Bin], Liu, B.Y.[Bo-Yang], Wang, H.C.[Hua-Chun], Qi, S.[Shuai], Chen, D.[Duo], Wang, P.[Peng], Wang, K.[Kuiru], Sang, X.Z.[Xin-Zhu],
Improved real-time three-dimensional stereo matching with local consistency,
IVC(124), 2022, pp. 104509.
Elsevier DOI 2208
Image matching, Disparity refinement, Local consistency, Real-time BibRef

Zhang, H.Y.[Hao-Yuan], Chau, L.P.[Lap-Pui], Wang, D.[Danwei],
Soft Warping Based Unsupervised Domain Adaptation for Stereo Matching,
MultMed(24), 2022, pp. 3835-3846.
IEEE DOI 2208
Training, Task analysis, Pipelines, Neural networks, Adversarial machine learning, Feature extraction, soft warping loss BibRef

Gong, D.[Danchao], Huang, X.[Xu], Zhang, J.[Jidan], Yao, Y.X.[Yong-Xiang], Han, Y.L.[Yi-Long],
Efficient and Robust Feature Matching for High-Resolution Satellite Stereos,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Zeng, K.[Kai], Wang, Y.N.[Yao-Nan], Zhu, Q.[Qing], Mao, J.X.[Jian-Xu], Zhang, H.[Hui],
Deep Progressive Fusion Stereo Network,
ITS(23), No. 12, December 2022, pp. 25437-25447.
IEEE DOI 2212
Costs, Feature extraction, Autonomous vehicles, Semantics, Task analysis, Estimation, Redundancy, Stereo matching, unary feature maps BibRef

Zeng, K.[Kai], Wang, Y.N.[Yao-Nan], Wang, W.[Wei], Zhang, H.[Hui], Mao, J.X.[Jian-Xu], Zhu, Q.[Qing],
Deep Confidence Propagation Stereo Network,
ITS(24), No. 8, August 2023, pp. 8097-8108.
IEEE DOI 2308
Costs, Feature extraction, Estimation, Correlation, Computer architecture, Measurement, Volume measurement, unary feature maps BibRef

Dinh, V.Q.[Vinh Quang], Choi, T.J.[Tae Jong],
StereoPairFree: Self-Constructed Stereo Correspondence Network From Natural Images,
IEEE_Int_Sys(38), No. 1, January 2023, pp. 19-33.
IEEE DOI 2303
Costs, Training, Pipelines, Distortion, Deep learning, Pattern matching, Lighting BibRef

Gan, W.[Wanshui], Wu, W.H.[Wen-Hao], Chen, S.F.[Shi-Feng], Zhao, Y.X.[Yu-Xiang], Wong, P.K.[Pak Kin],
Rethinking 3D cost aggregation in stereo matching,
PRL(167), 2023, pp. 75-81.
Elsevier DOI 2303
Stereo matching, Disparity estimation, Shift operation, 3D Convolution BibRef

zihao, Z.[Zhang], Ying, N.[Niu], Fanman, M.[Meng], Tiejun, Y.[Yang], Chao, F.[Fan], Xiao-Zhen, R.[Ren], Rui-Qi, W.[Wu], Kun, C.[Cao], Haocheng, W.[Wang],
Multi-directional broad learning system for the unsupervised stereo matching method,
PR(142), 2023, pp. 109648.
Elsevier DOI 2307
Multi-directional broad learning system, Unsupervised stereo matching, Local gravity weight method BibRef

Qian, R.[Ren], Feng, R.[Renyan], Xie, W.D.[Wang-Duo], Yang, W.B.[Wen-Bang], Zhao, Y.[Yong],
MFF: An effective method of solving the ill regions in stereo matching,
IET-CV(17), No. 6, 2023, pp. 615-625.
DOI Link 2310
convolutional neural nets, stereo image processing BibRef

Wang, Q.Y.[Qing-Yu], Xing, H.[Hao], Ying, Y.[Yibin], Zhou, M.C.[Ming-Chuan],
CGFNet: 3D Convolution Guided and Multi-scale Volume Fusion Network for fast and robust stereo matching,
PRL(173), 2023, pp. 38-44.
Elsevier DOI 2310
Robotic vision, Stereo matching, Disparity estimation, Deep learning, Textureless regions BibRef

Li, Z.Z.[Zi-Zhuo], Ma, J.Y.[Jia-Yi], Xiao, G.[Guobao],
Density-Guided Incremental Dominant Instance Exploration for Two-View Geometric Model Fitting,
IP(32), 2023, pp. 5408-5422.
IEEE DOI 2310
BibRef

Fang, I.S.[I-Sheng], Wen, H.C.[Hsiao-Chieh], Hsu, C.L.[Chia-Lun], Jen, P.C.[Po-Chung], Chen, P.Y.[Ping-Yang], Chen, Y.S.[Yong-Sheng],
ES3Net: Accurate and Efficient Edge-based Self-Supervised Stereo Matching Network,
EVW23(4472-4481)
IEEE DOI 2309
BibRef

Chebbi, M.A.[Mohamed Ali], Rupnik, E.[Ewelina], Pierrot-Deseilligny, M.[Marc], Lopes, P.[Paul],
DeepSim-Nets: Deep Similarity Networks for Stereo Image Matching,
EarthVision23(2097-2105)
IEEE DOI 2309
BibRef

Zhao, H.L.[Hao-Liang], Zhou, H.[Huizhou], Zhang, Y.J.[Yong-Jun], Chen, J.[Jie], Yang, Y.T.[Yi-Tong], Zhao, Y.[Yong],
High-Frequency Stereo Matching Network,
CVPR23(1327-1336)
IEEE DOI 2309
BibRef

Song, T.Y.[Tae-Yong], Kim, S.[Sunok], Sohn, K.H.[Kwang-Hoon],
Unsupervised Deep Asymmetric Stereo Matching with Spatially-Adaptive Self-Similarity,
CVPR23(13672-13680)
IEEE DOI 2309
BibRef

Rao, Z.B.[Zhi-Bo], Xiong, B.S.[Bang-Shu], He, M.Y.[Ming-Yi], Dai, Y.C.[Yu-Chao], He, R.J.[Ren-Jie], Shen, Z.[Zhelun], Li, X.[Xing],
Masked Representation Learning for Domain Generalized Stereo Matching,
CVPR23(5435-5444)
IEEE DOI 2309
BibRef

Chang, T.Y.[Tian-Yu], Yang, X.[Xun], Zhang, T.Z.[Tian-Zhu], Wang, M.[Meng],
Domain Generalized Stereo Matching via Hierarchical Visual Transformation,
CVPR23(9559-9568)
IEEE DOI 2309
BibRef

Zhao, H.L.[Hao-Liang], Zhou, H.[Huizhou], Zhang, Y.J.[Yong-Jun], Zhao, Y.[Yong], Yang, Y.T.[Yi-Tong], Ouyang, T.[Ting],
EAI-stereo: Error Aware Iterative Network for Stereo Matching,
ACCV22(I:3-19).
Springer DOI 2307
BibRef

Pilzer, A.[Andrea], Hou, Y.X.[Yu-Xin], Loppi, N.[Niki], Solin, A.[Arno], Kannala, J.H.[Ju-Ho],
Expansion of Visual Hints for Improved Generalization in Stereo Matching,
WACV23(5829-5838)
IEEE DOI 2302
Symbiosis, Visualization, Solid modeling, Laser radar, Robustness, Sensors, Algorithms: 3D computer vision BibRef

Brousseau, P.A.[Pierre-André], Roy, S.[Sébastien],
A Permutation Model for the Self-Supervised Stereo Matching Problem,
CRV22(122-131)
IEEE DOI 2301
Instruments, Estimation, Self-supervised learning, Standards, Testing, Autonomous robots, Permutation, Stereo, Self-Supervised, Occlusions BibRef

Fan, X.L.[Xiu-Le], Jeon, S.[Soo], Fidan, B.[Baris],
Occlusion-Aware Self-Supervised Stereo Matching with Confidence Guided Raw Disparity Fusion,
CRV22(132-139)
IEEE DOI 2301
Deep learning, Training, Pipelines, Neural networks, Robot vision systems, Prediction algorithms, Cameras, robot vision BibRef

Xie, Z.J.[Zhi-Jie], Rao, Y.[Yuan], Hu, Y.Q.[Ye-Qi], Fan, H.[Hao], Qi, L.[Lin], Dong, J.Y.[Jun-Yu],
Cascaded Feature Interaction Network for Stereo Matching,
ICIVC22(312-318)
IEEE DOI 2301
Costs, Fuses, Memory management, Network architecture, Benchmark testing, Task analysis, stereo matching, disparity range, feature interaction BibRef

Liu, J.Z.[Jia-Zhi], Liu, F.[Feng],
Robust Stereo Matching with an Unfixed and Adaptive Disparity Search Range,
ICPR22(4016-4022)
IEEE DOI 2212
Costs, Redundancy, Memory architecture, Feature extraction BibRef

Kim, K.[Kwonyoung], Park, J.[Jungin], Lee, J.Y.[Ji-Young], Min, D.B.[Dong-Bo], Sohn, K.H.[Kwang-Hoon],
PointFix: Learning to Fix Domain Bias for Robust Online Stereo Adaptation,
ECCV22(XXXVIII:568-585).
Springer DOI 2211
BibRef

Ye, S.Q.[Shui-Qiang], Zeng, P.C.[Peng-Cheng], Li, P.F.[Peng-Fei], Wang, W.Q.[Wei-Qi], Xinan, W.[Wang], Zhao, Y.[Yong],
MLP-Stereo: Heterogeneous Feature Fusion in MLP for Stereo Matching,
ICIP22(101-105)
IEEE DOI 2211
Costs, Convolution, Real-time systems, Stereo matching, MLP, cost aggregation, inductive bias, real-time network BibRef

Li, J.K.[Jian-Kun], Wang, P.[Peisen], Xiong, P.F.[Peng-Fei], Cai, T.[Tao], Yan, Z.[Ziwei], Yang, L.[Lei], Liu, J.[Jiangyu], Fan, H.Q.[Hao-Qiang], Liu, S.C.[Shuai-Cheng],
Practical Stereo Matching via Cascaded Recurrent Network with Adaptive Correlation,
CVPR22(16242-16251)
IEEE DOI 2210
Correlation, Adaptive systems, Training data, Benchmark testing, Network architecture, Real-time systems, Pattern recognition, Low-level vision BibRef

Kang, D.[Donghun], Jang, H.[Hyeonjoong], Lee, J.[Jungeon], Kyung, C.M.[Chong-Min], Kim, M.H.[Min H.],
Uniform Subdivision of Omnidirectional Camera Space for Efficient Spherical Stereo Matching,
CVPR22(12962-12970)
IEEE DOI 2210
Geometry, Image resolution, Image edge detection, Memory management, Optical distortion, Cameras, Distortion, Low-level vision BibRef

Xu, G.W.[Gang-Wei], Cheng, J.[Junda], Guo, P.[Peng], Yang, X.[Xin],
Attention Concatenation Volume for Accurate and Efficient Stereo Matching,
CVPR22(12971-12980)
IEEE DOI 2210
Weight measurement, Matched filters, Costs, Correlation, Volume measurement, Computer network reliability, Low-level vision BibRef

Lipson, L.[Lahav], Teed, Z.[Zachary], Deng, J.[Jia],
RAFT-Stereo: Multilevel Recurrent Field Transforms for Stereo Matching,
3DV21(218-227)
IEEE DOI 2201
Convolutional codes, Deep architecture, Transforms, Benchmark testing, Real-time systems, Optical flow, Stereo, Matching, GRU BibRef

Sarrazin, E., Cournet, M., Dumas, L., Defonte, V., Fardet, Q., Steux, Y., Diaz, N.J.[N. Jimenez], Dubois, E., Youssefi, D., Buffe, F.,
Ambiguity Concept In Stereo Matching Pipeline,
ISPRS21(B2-2021: 383-390).
DOI Link 2201
BibRef

Wang, H.[Hengli], Fan, R.[Rui], Liu, M.[Ming],
SCV-Stereo: Learning Stereo Matching from a Sparse Cost Volume,
ICIP21(3203-3207)
IEEE DOI 2201
Training, Image processing, Estimation, Benchmark testing, Computational efficiency, stereo matching, sparse cost volume representation BibRef

Wang, H.[Hengli], Fan, R.[Rui], Liu, M.[Ming],
Co-Teaching: an Ark to Unsupervised Stereo Matching,
ICIP21(3328-3332)
IEEE DOI 2201
Image processing, Benchmark testing, Robustness, Autonomous vehicles, stereo matching, unsupervised learning, co-teaching strategy BibRef

Guo, W.[Wei], Zhu, Z.[Ziyu], Xia, F.[Fukun], Sun, J.R.[Jia-Rui], Zhao, Y.[Yong],
Hierarchical and Multi-Level Cost Aggregation for Stereo Matching,
ICIP21(2863-2867)
IEEE DOI 2201
Deep learning, Image processing, Estimation, Robustness, Convolutional neural networks, Stereo matching, hierarchical, refined disparity map BibRef

Heidari, S.[Shahrokh], Rogers, M.[Mitchell], Delmas, P.[Patrice],
An Improved Quantum Solution for the Stereo Matching Problem,
IVCNZ21(1-6)
IEEE DOI 2201
Geometry, Annealing, NP-hard problem, Qubit, Quantum mechanics, Quantum annealing, Search problems, Quantum annealing, D-Wave, Stereo matching BibRef

Wang, H.[Hewei], Pathan, M.S.[Muhammad Salman], Dev, S.[Soumyabrata],
Stereo Matching Based on Visual Sensitive Information,
ICIVC21(312-316)
IEEE DOI 2112
Visualization, Costs, Codes, Heuristic algorithms, Computational modeling, Standards, Middlebury dataset BibRef

Xie, L.[Lei], Ma, L.[Lei], Jiang, D.[Dong], Fei, Q.G.[Qing-Guo],
Non-common Field of View 2D Full-Field Digital Image Correlation Method Based on Space Conversion Calibration Method,
ICIVC21(222-226)
IEEE DOI 2112
Coordinate measuring machines, Correlation, Digital images, Displacement measurement, Cameras, camera calibration BibRef

Xu, B.[Bin], Xu, Y.H.[Yu-Hua], Yang, X.L.[Xiao-Li], Jia, W.[Wei], Guo, Y.L.[Yu-Lan],
Bilateral Grid Learning for Stereo Matching Networks,
CVPR21(12492-12501)
IEEE DOI 2111
Costs, Codes, Navigation, Estimation, Complex networks, Network architecture BibRef

Shen, Z.[Zhelun], Dai, Y.C.[Yu-Chao], Rao, Z.B.[Zhi-Bo],
CFNet: Cascade and Fused Cost Volume for Robust Stereo Matching,
CVPR21(13901-13910)
IEEE DOI 2111
Training, Costs, Uncertainty, Image resolution, Codes, Estimation BibRef

Yao, C.T.[Cheng-Tang], Jia, Y.D.[Yun-De], Di, H.J.[Hui-Jun], Li, P.X.[Peng-Xiang], Wu, Y.W.[Yu-Wei],
A Decomposition Model for Stereo Matching,
CVPR21(6087-6096)
IEEE DOI 2111
Costs, Fuses, Computational modeling, Face recognition, Pipelines, Estimation BibRef

Zhang, D.[Doudou], Cai, J.[Jing], Xue, Y.B.[Yan-Bing], Gao, Z.[Zan], Zhang, H.[Hua],
Attention Stereo Matching Network,
ICPR21(4973-4980)
IEEE DOI 2105
Geometry, Correlation, Benchmark testing, Real-time systems, Spatial resolution BibRef

Yang, Z.[Zuliu], Ai, X.D.[Xin-Dong], Yang, W.[Weida], Zhao, Y.[Yong], Dai, Q.F.[Qi-Fei], Li, F.[Fuchi],
Deeply-fused Attentive Network for Stereo Matching,
ICPR21(1717-1724)
IEEE DOI 2105
Fuses, Logic gates, Feature extraction, Prediction algorithms, Encoding BibRef

Wang, H.Y.[Hai-Yang], Wang, X.C.[Xin-Chao], Song, J.[Jie], Lei, J.[Jie], Song, M.L.[Ming-Li],
Faster Self-adaptive Deep Stereo,
ACCV20(I:175-191).
Springer DOI 2103
BibRef

Chen, S.Y.[Shu-Ya], Xiang, Z.Y.[Zhi-Yu], Qiao, C.Y.[Cheng-Yu], Chen, Y.M.[Yi-Man], Bai, T.M.[Ting-Ming],
Sgnet: Semantics Guided Deep Stereo Matching,
ACCV20(I:106-122).
Springer DOI 2103
BibRef

Sinha, A.[Ayan], Murez, Z.[Zak], Bartolozzi, J.[James], Badrinarayanan, V.[Vijay], Rabinovich, A.[Andrew],
Deltas: Depth Estimation by Learning Triangulation and Densification of Sparse Points,
ECCV20(XXI:104-121).
Springer DOI 2011
BibRef

Liu, Y., Ren, J., Zhang, J., Liu, J., Lin, M.,
Visually Imbalanced Stereo Matching,
CVPR20(2026-2035)
IEEE DOI 2008
Cameras, Visualization, Radio frequency, Prediction algorithms, Sensors, Image resolution BibRef

Kallwies, J., Engler, T., Forkel, B., Wuensche, H.,
Triple-SGM: Stereo Processing using Semi-Global Matching with Cost Fusion,
WACV20(192-200)
IEEE DOI 2006
Cameras, Transforms, Real-time systems, Interpolation, Stereo vision, Robustness, Transmission line matrix methods BibRef

Armeni, I., He, Z., Zamir, A., Gwak, J., Malik, J., Fischer, M., Savarese, S.,
3D Scene Graph: A Structure for Unified Semantics, 3D Space, and Camera,
ICCV19(5663-5672)
IEEE DOI 2004
cameras, graph theory, image registration, image representation, image retrieval, stereo image processing, illumination type, BibRef

Nie, G.Y.[Guang-Yu], Cheng, M.M.[Ming-Ming], Liu, Y.[Yun], Liang, Z.F.[Zheng-Fa], Fan, D.P.[Deng-Ping], Liu, Y.[Yue], Wang, Y.T.[Yong-Tian],
Multi-Level Context Ultra-Aggregation for Stereo Matching,
CVPR19(3278-3286).
IEEE DOI 2002
BibRef

Poggi, M.[Matteo], Pallotti, D.[Davide], Tosi, F.[Fabio], Mattoccia, S.[Stefano],
Guided Stereo Matching,
CVPR19(979-988).
IEEE DOI 2002
BibRef

Lai, H.Y.[Hsueh-Ying], Tsai, Y.H.[Yi-Hsuan], Chiu, W.C.[Wei-Chen],
Bridging Stereo Matching and Optical Flow via Spatiotemporal Correspondence,
CVPR19(1890-1899).
IEEE DOI 2002
BibRef

Yang, G.[Guorun], Deng, Z.D.[Zhi-Dong], Lu, H.C.[Hong-Chao], Li, Z.P.[Ze-Ping],
SRC-Disp: Synthetic-Realistic Collaborative Disparity Learning for Stereo Matching,
ACCV18(V:707-723).
Springer DOI 1906
BibRef

Batsos, K.[Konstantinos], Cai, C.J.[Chang-Jiang], Mordohai, P.[Philippos],
CBMV: A Coalesced Bidirectional Matching Volume for Disparity Estimation,
CVPR18(2060-2069)
IEEE DOI 1812
Optimization, Training, Pipelines, Estimation, Forestry, Benchmark testing BibRef

Jie, Z., Wang, P., Ling, Y., Zhao, B., Wei, Y., Feng, J., Liu, W.,
Left-Right Comparative Recurrent Model for Stereo Matching,
CVPR18(3838-3846)
IEEE DOI 1812
Estimation, Computational modeling, Predictive models, Pipelines, Road transportation, Solid modeling, Feature extraction BibRef

Luo, Y., Ren, J., Lin, M., Pang, J., Sun, W., Li, H., Lin, L.,
Single View Stereo Matching,
CVPR18(155-163)
IEEE DOI 1812
Estimation, Pipelines, Task analysis, Training, Image reconstruction, Cameras BibRef

Zhu, A.Z.[Alex Zihao], Chen, Y.[Yibo], Daniilidis, K.[Kostas],
Realtime Time Synchronized Event-Based Stereo,
ECCV18(VI: 438-452).
Springer DOI 1810
Stereo with motion blur. BibRef

Paget, M., Tarel, J.P., Monasse, P.,
Stereo ambiguity index for semi-global matching,
ICIP17(2513-2517)
IEEE DOI 1803
Covariance matrices, Dynamic programming, Image reconstruction, Indexes, Optimization, Task analysis, Uncertainty, Uncertainty index BibRef

Peng, X., Bouzerdoum, A., Phung, S.L.,
An efficient local method for stereo matching using daisy features,
ICIP17(2503-2507)
IEEE DOI 1803
Cost function, Distortion measurement, Estimation, Machine learning, Nickel, Optimization methods, local optimization, the DAISY feature vector BibRef

Navarro, J., Buades, A.,
Disparity adapted weighted aggregation for local stereo,
ICIP17(2249-2253)
IEEE DOI 1803
Colored noise, Estimation, Image color analysis, Robustness, Shape, Stereo, adaptive support weights, block-matching, disparity estimation BibRef

Bushnevskiy, A.[Andrey], Sorgi, L.[Lorenzo], Rosenhahn, B.[Bodo],
Feature Points Densification and Refinement,
CIAP17(I:530-538).
Springer DOI 1711
BibRef

Shaked, A., Wolf, L.B.[Lior B.],
Improved Stereo Matching with Constant Highway Networks and Reflective Confidence Learning,
CVPR17(6901-6910)
IEEE DOI 1711
Benchmark testing, Network architecture, Neural networks, Pipelines, Road transportation, Training BibRef

Li, X.H.[Xiao-Han], Song, Z.X.[Zong-Xi],
Optimization on stereo correspondence based on local feature algorithm,
ICIVC17(113-117)
IEEE DOI 1708
Algorithm design and analysis, Detectors, Euclidean distance, Feature extraction, Image matching, Mathematical model, Robustness, binocular stereovision, feature point extraction, scale invariant feature transform, speeded-up robust feature, stereo correspondence BibRef

Yao, P.[Peng], Zhang, H.[Hua], Xue, Y.B.[Yan-Bing], Chen, S.Y.[Sheng-Yong],
AGO: Accelerating Global Optimization for Accurate Stereo Matching,
MMMod18(I:67-80).
Springer DOI 1802
BibRef

Han, P.X.[Pu-Xia], Zhao, M.[Meng], Chen, S.Y.[Sheng-Yong],
Fusion of texture, color and gradient information for stereo matching cost computation,
ICIVC17(118-121)
IEEE DOI 1708
Algorithm design and analysis, Error analysis, Filtering algorithms, Image color analysis, Matched filters, Pattern matching, HA algorithm, cost aggregation, multi-feature space, stereo matching BibRef

Kitagawa, M., Shimizu, I., Sara, R.,
High accuracy local stereo matching using DoG scale map,
MVA17(258-261)
DOI Link 1708
Dogs, Filtering algorithms, Image edge detection, Kernel, Matched filters, Smoothing methods BibRef

Bustos, C.[Cristina], Vargas, E.[Elizabeth], Trujillo, M.[Maria],
Classifying Estimated Stereo Correspondences Based on Delaunay Triangulation,
CIARP16(417-425).
Springer DOI 1703
BibRef

Poggi, M.[Matteo], Mattoccia, S.[Stefano],
Evaluation of variants of the SGM algorithm aimed at implementation on embedded or reconfigurable devices,
IC3D16(1-8)
IEEE DOI 1703
Semi Global Matching. Dense depth from stereo. computer vision BibRef

Thai, B.[Ba], Al-Nasrawi, M.[Mukhalad], Deng, G.[Guang], Ross, R.[Robert], Huynh, P.[Phat],
Constrained Smoothness Cost in Markov Random Field Based Stereo Matching,
DICTA16(1-5)
IEEE DOI 1701
Approximation algorithms BibRef

Gaisser, F., Jonker, P.P., Chiba, T.,
Image Registration for Placenta Reconstruction,
WBIR16(473-480)
IEEE DOI 1612
BibRef

Duggal, S., Wang, S., Ma, W., Hu, R., Urtasun, R.,
DeepPruner: Learning Efficient Stereo Matching via Differentiable PatchMatch,
ICCV19(4383-4392)
IEEE DOI 2004
image matching, inference mechanisms, learning (artificial intelligence), stereo image processing, Computational modeling BibRef

Luo, W., Schwing, A.G., Urtasun, R.[Raquel],
Efficient Deep Learning for Stereo Matching,
CVPR16(5695-5703)
IEEE DOI 1612
BibRef

Jeon, H.G., Lee, J.Y., Im, S., Ha, H., Kweon, I.S.,
Stereo Matching with Color and Monochrome Cameras in Low-Light Conditions,
CVPR16(4086-4094)
IEEE DOI 1612
BibRef

Zou, D., Guo, P., Wang, Q., Wang, X., Shao, G., Shi, F., Li, J., Park, P.K.J.,
Context-aware event-driven stereo matching,
ICIP16(1076-1080)
IEEE DOI 1610
Biosensors BibRef

Kim, K.R., Kim, C.S.,
Adaptive smoothness constraints for efficient stereo matching using texture and edge information,
ICIP16(3429-3433)
IEEE DOI 1610
Algorithm design and analysis BibRef

Nahar, S., Joshi, M.V.,
Dense disparity estimation based on feature matching and IGMRF regularization,
ICPR16(3804-3809)
IEEE DOI 1705
BibRef
Earlier:
A regularization framework for stereo matching using IGMRF prior and sparseness learned from autoencoder,
ICIP16(3434-3438)
IEEE DOI 1610
BibRef
Earlier:
A learning based approach for dense stereo matching with IGMRF prior,
NCVPRIPG13(1-4)
IEEE DOI 1408
Gaussian processes. Estimation, Feature extraction, Image edge detection, Image segmentation, Minimization, Robustness, Training. Discrete cosine transforms BibRef

Hamilton, O.K., Breckon, T.P.[Toby P.],
Generalized dynamic object removal for dense stereo vision based scene mapping using synthesised optical flow,
ICIP16(3439-3443)
IEEE DOI 1610
Cameras BibRef

Chuang, T.Y., Ting, H.W., Jaw, J.J.,
Hybrid-based Dense Stereo Matching,
ISPRS16(B3: 495-501).
DOI Link 1610
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Monteiro, N.B.[Nuno Barroso], Barreto, J.P.[João Pedro], Gaspar, J.[José],
Dense Lightfield Disparity Estimation Using Total Variation Regularization,
ICIAR16(462-469).
Springer DOI 1608
BibRef

Suvei, S.D.[Stefan-Daniel], Bodenhagen, L.[Leon], Kiforenko, L.[Lilita], Christiansen, P.[Peter], Jørgensen, R.N.[Rasmus N.], Buch, A.G.[Anders G.], Krüger, N.[Norbert],
Stereo and Active-Sensor Data Fusion for Improved Stereo Block Matching,
ICIAR16(451-461).
Springer DOI 1608
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Davies, R., Wilson, I., Ware, A.,
Stereoscopic disparity generation reduction using a dilated Laplacian approach,
WSSIP15(101-104)
IEEE DOI 1603
Laplace equations BibRef

Cheng, H., Zhang, J., An, P., Liu, Z.,
A Novel Saliency Model for Stereoscopic Images,
DICTA15(1-7)
IEEE DOI 1603
Boolean functions BibRef

Chen, Z., Sun, X., Wang, L., Yu, Y., Huang, C.,
A Deep Visual Correspondence Embedding Model for Stereo Matching Costs,
ICCV15(972-980)
IEEE DOI 1602
Computational modeling BibRef

Lin, H.Y.[Huei-Yung], Kao, C.C.[Chung-Chieh],
Stereo Matching Techniques for High Dynamic Range Image Pairs,
PSIVT15(605-616).
Springer DOI 1602
BibRef

Facciolo, G.[Gabriele], de Franchis, C.[Carlo], Meinhardt, E.[Enric],
MGM: A Significantly More Global Matching for Stereovision,
BMVC15(xx-yy).
DOI Link 1601
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Khan, W.[Waqar], Klette, R.[Reinhard],
Stereo-Matching in the Context of Vision-Augmented Vehicles,
ISVC15(II: 57-69).
Springer DOI 1601
BibRef

Donne, S.[Simon], Goossens, B.[Bart], Philips, W.[Wilfried],
Point Triangulation through Polyhedron Collapse Using the L-inf Norm,
ICCV15(792-800)
IEEE DOI 1602
AWGN BibRef

Ma, R.[Rui], Au, O.C., Wan, P.F.[Peng-Fei], Sun, W.X.[Wen-Xiu], Xu, L.F.[Ling-Feng], Jia, L.H.[Lu-Heng],
Solving dense stereo matching via quadratic programming,
VCIP14(370-373)
IEEE DOI 1504
computational complexity BibRef

Rosales, E., Guan, L.[Ling],
Stereo correspondence using an assisted discrete cosine transform method,
VCIP14(81-84)
IEEE DOI 1504
discrete cosine transforms BibRef

Wei, D.L.[Dong-Lai], Liu, C.[Ce], Freeman, W.T.[William T.],
A Data-Driven Regularization Model for Stereo and Flow,
3DV14(277-284)
IEEE DOI 1503
Benchmark testing BibRef

Furuta, R.[Ryosuke], Ikehata, S.[Satoshi], Yamasaki, T.[Toshihiko], Aizawa, K.[Kiyoharu],
Coarse-to-fine strategy for efficient cost-volume filtering,
ICIP14(3793-3797)
IEEE DOI 1502
Accuracy BibRef

Bai, X.J.[Xue-Jiao], Luo, X.[Xuan], Li, S.[Shuo], Lu, H.T.[Hong-Tao],
Adaptive stereo matching via loop-erased random walk,
ICIP14(3788-3792)
IEEE DOI 1502
Accuracy BibRef

Ha, J.[Jeong_Mok], Jeong, H.[Hong],
A Robust Stereo Vision with Confidence Measure Based on Tree Agreement,
PSIVT15(243-256).
Springer DOI 1602
BibRef

Ha, J.[Jeong_Mok], Jeon, J.[Jea_Young], Bae, G.[Gi_Yeong], Jo, S.[Sung_Yong], Jeong, H.[Hong],
Cost Aggregation Table: Cost Aggregation Method Using Summed Area Table Scheme for Dense Stereo Correspondence,
ISVC14(I: 815-826).
Springer DOI 1501
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Olsson, C.[Carl], Ulen, J.[Johannes], Eriksson, A.[Anders],
Local Refinement for Stereo Regularization,
ICPR14(4056-4061)
IEEE DOI 1412
Least squares approximations BibRef

Huang, X.M.[Xiao-Ming], Cui, G.Q.[Guo-Qin], Zhang, Y.D.[Yun-Dong],
An Improved Filtering for Fast Stereo Matching,
ICPR14(2448-2452)
IEEE DOI 1412
Accuracy BibRef

Cheng, J.[Jian], Leng, C.[Cong], Wu, J.X.[Jia-Xiang], Cui, H.N.[Hai-Nan], Lu, H.Q.[Han-Qing],
Fast and Accurate Image Matching with Cascade Hashing for 3D Reconstruction,
CVPR14(1-8)
IEEE DOI 1409
BibRef

Ito, K., Sasaki, M., Aoki, T., Ishigami, T., Nishimura, A.,
Generating Robust and Stable Disparity Map Using Phase-Based Correspondence Matching from Stereo Video Sequence,
ACPR13(586-590)
IEEE DOI 1408
image matching
See also Palmprint Recognition Algorithm Using Phase-Based Correspondence Matching, A.
See also Fingerprint Recognition Algorithm Using Phase-Based Image Matching for Low-Quality Fingerprints, A.
See also Effective Approach for Iris Recognition Using Phase-Based Image Matching, An. BibRef

Wang, H.Q.[Hao-Qian], Wu, M.[Mian], Zhang, Y.B.[Yong-Bing], Zhang, L.[Lei],
Effective stereo matching using reliable points based graph cut,
VCIP13(1-6)
IEEE DOI 1402
graph theory BibRef

Hong, G.S.[Gwang-Soo], Kim, B.G.[Byung-Gyu], Kim, T.J.[Tae-Jung], Yu, J.J.[Jeong-Ju],
Efficient depth map estimation method based on gradient weight cost aggregation strategy,
VCIP13(1-5)
IEEE DOI 1402
image matching BibRef

Liu, H.[Haixu], Liu, Y.[Yang], OuYang, S.X.[Shu-Xin], Liu, C.Y.[Chen-Yu], Li, X.M.[Xue-Ming],
A novel method for stereo matching using Gabor Feature Image and Confidence Mask,
VCIP13(1-6)
IEEE DOI 1402
Gabor filters BibRef

Heise, P.[Philipp], Jensen, B.[Brian], Klose, S.[Sebastian], Knoll, A.[Alois],
Variational PatchMatch MultiView Reconstruction and Refinement,
ICCV15(882-890)
IEEE DOI 1602
BibRef
Earlier: A1, A3, A2, A4:
PM-Huber: PatchMatch with Huber Regularization for Stereo Matching,
ICCV13(2360-2367)
IEEE DOI 1403
PatchMatch. Cameras BibRef

Shin, Y.H.[Yong-Ho], Yoon, K.J.[Kuk-Jin],
Spatiotemporal Stereo Matching with 3D Disparity Profiles,
BMVC15(xx-yy).
DOI Link 1601
BibRef
Earlier:
Spatiotemporal stereo matching for dynamic scenes with temporal disparity variation,
ICIP13(2242-2246)
IEEE DOI 1402
Belief propagation; Image sequences; Markov random fields; Stereo vision BibRef

Fuhr, G., Fickel, G.P., Dal'Aqua, L.P., Jung, C.R., Malzbender, T., Samadani, R.,
An evaluation of stereo matching methods for view interpolation,
ICIP13(403-407)
IEEE DOI 1402
Computer vision BibRef

Bai, X.J.[Xue-Jiao], Kamata, S.I.[Sei-Ichiro],
An efficient window-based stereo matching algorithm using foreground disparity concentration,
ICARCV12(1352-1357).
IEEE DOI 1304
BibRef

Wu, W.[Wei], Wang, H.Q.[Hao-Qian],
Stereo matching using graph cuts: A 3D-Hough transformation approach,
ICARCV12(1160-1164).
IEEE DOI 1304
BibRef

Lin, H.Y.[Huei-Yung], Chou, X.H.[Xin-Han],
Stereo matching on low intensity quantization images,
ICPR12(2618-2621).
WWW Link. 1302
BibRef

Liu, T.L.[Tian-Liang], Dai, X.B.[Xiu-Bin], Huo, Z.Y.[Zhi-Yong], Zhu, X.C.[Xiu-Chang], Luo, L.M.[Li-Min],
A cost construction via MSW and linear regression for stereo matching,
ICPR12(914-917).
WWW Link. 1302
BibRef

Ma, J.[Jiayi], Zhao, J.[Ji], Zhou, Y.[Yu], Tian, J.W.[Jin-Wen],
Mismatch removal via coherent spatial mapping,
ICIP12(1-4).
IEEE DOI 1302
BibRef

Wang, C.[Chun], Sahin, E., Suominen, O.[Olli], Gotchev, A.[Atanas],
Depth estimation by combining stereo matching and coded aperture,
VCIP14(291-294)
IEEE DOI 1504
image matching BibRef

Suominen, O.[Olli], Gotchev, A.[Atanas], Hannuksela, M.M.[Miska M.],
Transform domain similarity measures in stereo matching,
3DTV12(1-4).
IEEE DOI 1212
BibRef

Zhu, S.Q.[Sheng-Qi], Zhang, L.[Li], Jin, H.L.[Hai-Lin],
A Locally Linear Regression Model for Boundary Preserving Regularization in Stereo Matching,
ECCV12(V: 101-115).
Springer DOI 1210
BibRef

Çlgla, C.[Cevahir], Alatan, A.A.[A. Aydln],
An Improved Stereo Matching Algorithm with Ground Plane and Temporal Smoothness Constraints,
UnOptFlow12(II: 134-147).
Springer DOI 1210
BibRef

Hirschmüller, H., Buder, M., Ernst, I.,
Memory Efficient Semi-Global Matching,
AnnalsPRS(I-3), No. 2012, pp. 371-376.
DOI Link 1209
BibRef

Irschara, A., Rumpler, M., Meixner, P., Pock, T., Bischof, H.,
Efficient and Globally Optimal Multi View Dense Matching for Aerial Images,
AnnalsPRS(I-3), No. 2012, pp. 227-232.
DOI Link 1209
BibRef

Hu, T., Wu, H.,
Dense Corresponding Pixel Matching Using A Fixed Window with RGB Independent Information,
AnnalsPRS(I-4), No. 2012, pp. 89-93.
DOI Link 1209
BibRef

Xiong, J., Zhang, Y.,
Combined Multi-View Matching Algorithm With Long-Strips of Satellite Imagery from Different Orbits,
AnnalsPRS(I-3), No. 2012, pp. 87-92.
DOI Link 1209
BibRef

Chang, W.C., Chen, L.C.,
Feature Analysis for Multi-Window Matching,
ISPRS12(XXXIX-B6:107-110).
DOI Link 1209
Center, Left, Right image. BibRef

Kumar, S.[Sanoj], Kumar, S.[Sanjeev], Sukavanam, N.[Nagarajan], Raman, B.[Balasubramanian],
Disparity estimation using fractional dual tree complex wavelet transform,
ICIIP11(1-6).
IEEE DOI 1112
BibRef

Jama, A.[Arshad], Rakshit, S.[Subrata],
Augmenting graph cut with TV-L1 approach for robust stereo matching,
ICIIP11(1-6).
IEEE DOI 1112
BibRef

Feldmann, A.[Anton], Krüger, L.[Lars], Kummert, F.[Franz],
An Evaluation on Estimators for Stochastic and Heuristic Based Cost Functions Using the Epipolar-Constraint,
MIRAGE11(40-50).
Springer DOI 1110
BibRef

Sun, X.[Xun], Mei, X.[Xing], Jiao, S.H.[Shao-Hui], Zhou, M.C.[Ming-Cai], Wang, H.T.[Hai-Tao],
Stereo Matching with Reliable Disparity Propagation,
3DIMPVT11(132-139).
IEEE DOI 1109
BibRef

Wang, L.[Liang], Yang, R.G.[Rui-Gang],
Global stereo matching leveraged by sparse ground control points,
CVPR11(3033-3040).
IEEE DOI 1106
BibRef

Liu, S.[Shubao], Cooper, D.B.[David B.],
A complete statistical inverse ray tracing approach to multi-view stereo,
CVPR11(913-920).
IEEE DOI 1106
BibRef

Yu, J.J.[Jung-Jae], Kim, H.D.[Hae-Dong], Jang, H.W.[Ho-Wook], Nam, S.W.[Seung-Woo],
A hybrid color matching between stereo image sequences,
3DTV11(1-4).
IEEE DOI 1105
BibRef

Samir, B.V.R., Il, N.S.[Na Sang], Kalia, R.[Robin],
Image matching with SIFT descriptor on affine normalized MSERs,
FCV11(1-4).
IEEE DOI 1102
Maximally stable extremal regions. BibRef

Yamaguchi, K.[Koichiro], Hazan, T.[Tamir], McAllester, D.[David], Urtasun, R.[Raquel],
Continuous Markov Random Fields for Robust Stereo Estimation,
ECCV12(V: 45-58).
Springer DOI 1210

See also Robust Monocular Epipolar Flow Estimation.
See also Efficient Joint Segmentation, Occlusion Labeling, Stereo and Flow Estimation. BibRef

Geiger, A.[Andreas], Roser, M.[Martin], Urtasun, R.[Raquel],
Efficient Large-Scale Stereo Matching,
ACCV10(I: 25-38).
Springer DOI 1011
BibRef

Krumnikl, M.[Michal],
Stereo Matching in Mean Shift Attractor Space,
ISVC10(III: 465-473).
Springer DOI 1011
BibRef

Doutre, C.[Colin], Nasiopoulos, P.[Panos],
Optimized contrast reduction for crosstalk cancellation in 3D displays,
3DTV11(1-4).
IEEE DOI 1105
BibRef

Doutre, C.[Colin], Nasiopoulos, P.[Panos],
A stereo matching data cost robust to blurring,
ICIP10(1773-1776).
IEEE DOI 1009
BibRef

Chang, Y.J.[Yao-Jen], Liu, H.H.[Hung-Hsun], Chen, T.H.[Tsu-Han],
Improving subpixel stereo matching with segment evolution,
ICIP10(1781-1784).
IEEE DOI 1009
BibRef

Zhang, Y.H.[Yu-Hang], Hartley, R.I.[Richard I.], Wang, L.[Lei],
Fast Multi-labelling for Stereo Matching,
ECCV10(III: 524-537).
Springer DOI 0109
BibRef

Nefian, A.V.[Ara V.], Husmann, K.[Kyle], Broxton, M.J.[Michael J.], To, V.[Vinh], Lundy, M.[Michael], Hancher, M.D.[Mattew D.],
A bayesian formulation for sub-pixel refinement in stereo orbital imagery,
ICIP09(2361-2364).
IEEE DOI 0911
BibRef

Ju, M.H.[Myung-Ho], Kang, H.B.[Hang-Bong],
A new method for stereo matching using pixel cooperative optimization,
ICIP09(2105-2108).
IEEE DOI 0911
BibRef

Ju, M.H.[Myung-Ho], Kang, H.B.[Hang-Bong],
Constant Time Stereo Matching,
IMVIP09(13-17).
IEEE DOI 0909
BibRef

Liu, Q.Q.[Qiang-Qiang], Luo, X.L.[Xi-Ling], Zhang, J.[Jun],
A New Method of Correspondence for Multiple Cameras Based on Texture Energy,
ICMV09(264-269).
IEEE DOI 0912
BibRef

Xie, Y.R.[Yi-Ran], Liu, N.J.[Nian-Jun], Liu, S.[Sheng], Barnes, N.,
Stereo Matching Using Sub-segmentation and Robust Higher-Order Graph Cut,
DICTA11(518-523).
IEEE DOI 1205
BibRef

Wang, Z.J.[Zhong-Jie], Chen, S.Y.[Sheng-Yong], Liu, S.[Sheng],
Stereo Correspondence with Global and Local Traits,
CISP09(1-4).
IEEE DOI 0910
BibRef

Smith, B.M.[Brandon M.], Zhang, L.[Li], Jin, H.L.[Hai-Lin],
Stereo matching with nonparametric smoothness priors in feature space,
CVPR09(485-492).
IEEE DOI 0906
Each point as a feature vector, match point clouds. BibRef

Shen, R.[Rui], Cheng, I.[Irene], Li, X.B.[Xiao-Bo], Basu, A.[Anup],
Stereo matching using random walks,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Somanath, G.[Gowri], Rohith, M.V., Metaxas, D.N.[Dmitris N.], Kambhamettu, C.[Chandra],
D-Clutter: Building object model library from unsupervised segmentation of cluttered scenes,
CVPR09(2783-2789).
IEEE DOI 0906
BibRef

Rohith, M.V., Kambhamettu, C.[Chandra],
Learning Image Structures for Optimizing Disparity Estimation,
ACCV10(III: 627-640).
Springer DOI 1011
BibRef

Rohith, M.V., Somanath, G.[Gowri], Kambhamettu, C.[Chandra], Geiger, C.[Cathleen], Finnegan, D.[David],
Modified Region Growing for Stereo of Slant and Textureless Surfaces,
ISVC10(I: 666-677).
Springer DOI 1011
BibRef
Earlier: A1, A2, A3, A4, Only:
Towards estimation of dense disparities from stereo images containing large textureless regions,
ICPR08(1-5).
IEEE DOI 0812
BibRef

Gherardi, R.[Riccardo],
Confidence-based cost modulation for stereo matching,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Narasimha, R.[Ramya], Arnaud, E.[Elise], Forbes, F.[Florence], Horaud, R.[Radu],
Disparity and normal estimation through alternating maximization,
ICIP10(2969-2972).
IEEE DOI 1009
BibRef
Earlier:
Cooperative disparity and object boundary estimation,
ICIP08(1784-1787).
IEEE DOI 0810
Combine in markovian framework. BibRef

Mayer, H.[Helmut],
Issues for Image Matching in Structure from Motion,
ISPRS08(B3a: 21 ff).
PDF File. 0807
BibRef

Silveira, M.T., Feitosa, R.Q., Jacobsen, K., Brito, J.L.N.S., Heckel, Y.,
A Hybrid Method for Stereo Image Matching,
ISPRS08(B1: 895 ff).
PDF File. 0807
BibRef

Chai, D.F.[Deng-Feng], Peng, Q.S.[Qun-Sheng],
Bilayer Stereo Matching,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Zureiki, A.[Ayman], Devy, M.[Michel], Chatila, R.[Raja],
Stereo Matching using Reduced-Graph Cuts,
ICIP07(I: 237-240).
IEEE DOI 0709
BibRef

Simhadri, V.[Vikram], Chandramani, P.[Premanand], Ozturk, Y.[Yusuf],
RASCor: Realtime Associative Stereo Correspondence,
ICIP07(VI: 197-200).
IEEE DOI 0709
BibRef

Sarkis, M.[Michel], Diepold, K.[Klaus],
Sparse stereo matching using belief propagation,
ICIP08(1780-1783).
IEEE DOI 0810
BibRef

Sarkis, M.[Michel], Dörfler, N.[Nikolas], Diepold, K.[Klaus],
Fast Adaptive Graph-Cuts Based Stereo Matching,
ACIVS07(818-827).
Springer DOI 0708
BibRef

Li, P.[Ping], Farin, D.[Dirk], Gunnewiek, R.K.[Rene Klein], de With, P.H.N.[Peter H. N.],
Texture-Independent Feature-Point Matching (TIFM) from Motion Coherence,
ACCV07(I: 789-799).
Springer DOI 0711
BibRef
And:
Descriptor-Free Smooth Feature-Point Matching for Images Separated by Small/Mid Baselines,
ACIVS07(427-438).
Springer DOI 0708
BibRef

Curtis, P.[Phillip], Payeur, P.[Pierre],
A Method for Dynamic Selection of Optimal Depth Measurements Acquisition with Random Access Range Sensors,
CRV13(311-318)
IEEE DOI 1308
Computers BibRef

Boyer, A.[Alain], Curtis, P.[Phillip], Payeur, P.[Pierre],
3D Modeling from Multiple Views with Integrated Registration and Data Fusion,
CRV09(252-259).
IEEE DOI 0905
BibRef

Payeur, P.[Pierre], Desjardins, D.[Danick],
Structured Light Stereoscopic Imaging with Dynamic Pseudo-random Patterns,
ICIAR09(687-696).
Springer DOI 0907
BibRef
Earlier: A2, A1:
Dense Stereo Range Sensing with Marching Pseudo-Random Patterns,
CRV07(216-226).
IEEE DOI 0705
BibRef

Petran, V., Merat, F.,
Stereoscopic Correspondence without Continuity Assumptions,
Southwest06(21-25).
IEEE DOI 0603
BibRef

Mozerov, M.G.[Mikhail G.],
An Effective Stereo Matching Algorithm with Optimal Path Cost Aggregation,
DAGM06(617-626).
Springer DOI 0610
BibRef

Sasaki, K.[Kan'ya], Kameda, S.[Seiji], Iwata, A.[Atsushi],
Stereo Matching Algorithm Using a Weighted Average of Costs Aggregated by Various Window Sizes,
ACCV06(II:771-780).
Springer DOI 0601
BibRef

Gong, R., Gimel'farb, G.L.[Georgy L.], Delmas, P.[Patrice],
Semi-global stereo matching under large and spatially variant perceptive deviations,
ICVNZ15(1-6)
IEEE DOI 1701
dynamic programming BibRef

Gimel'farb, G.L.[Georgy L.], Li, J.[Jiang], Morris, J.[John], Delmas, P.[Patrice],
Concurrent Stereo under Photometric Image Distortions,
ICPR06(I: 111-114).
IEEE DOI 0609
BibRef

Morris, J.[John], Gimel'farb, G.L.[Georgy L.], Liu, J.[Jiang], Delmas, P.[Patrice],
Concurrent Stereo Matching: An Image Noise-Driven Model,
EMMCVPR05(46-59).
Springer DOI 0601
BibRef

Meltzer, T.[Talya], Yanover, C.[Chen], Weiss, Y.[Yair],
Globally Optimal Solutions for Energy Minimization in Stereo Vision Using Reweighted Belief Propagation,
ICCV05(I: 428-435).
IEEE DOI 0510
Find the global optimum (generally NP complete) in 30 minutes using belief propogation approach. BibRef

Kong, D., Tao, H.,
Stereo Matching via Learning Multiple Experts Behaviors,
BMVC06(I:97).
PDF File. 0609
BibRef
Earlier:
A method for learning matching errors for stereo computation,
BMVC04(xx-yy).
HTML Version. 0508
BibRef

Ahlvers, U., Zoelzer, U.,
Improvement of phase-based algorithms for disparity estimation by means of magnitude information,
ICIP04(V: 3025-3028).
IEEE DOI 0505
BibRef

Ahlvers, U.[Udo], Zoelzer, U.[Udo], Rechmeier, S.[Stefan],
FFT-Based Disparity Estimation for Stereo Image Coding,
DAGM03(257-264).
Springer DOI 0310
BibRef
And: ICIP03(I: 761-764).
IEEE DOI 0312
BibRef

Jodoin, P.M., Mignotte, M.,
An energy-based framework using global spatial constraints for the stereo correspondence problem,
ICIP04(V: 3001-3004).
IEEE DOI 0505
BibRef

Jagmohan, A., Singh, M., Ahuja, N.,
Dense stereo matching using kernel maximum likelihood estimation,
ICPR04(III: 28-31).
IEEE DOI 0409
BibRef

Kostkova, J., Sara, R.,
Stratified Dense Matching for Stereopsis in Complex Scenes,
BMVC03(xx-yy).
HTML Version. 0409
BibRef

Baseski, E.[Emre], Pugeault, N.[Nicolas], Kalkan, S.[Sinan], Kraft, D.[Dirk], Worgotter, F.[Florentin], Kruger, N.[Norbert],
A Scene Representation Based on Multi-Modal 2D and 3D Features,
ICCV07(1-7).
IEEE DOI 0710

See also Utilizing Semantic Interpretation of Junctions for 3D-2D Pose Estimation. BibRef

Pugeault, N.[Nicolas], Worgotter, F.[Florentin], Kruger, N.[Norbert],
Multi-modal Scene Reconstruction using Perceptual Grouping Constraints,
PercOrg06(195).
IEEE DOI 0609
BibRef

Pugeault, N.[Nicolas], Kruger, N.[Norbert],
Multi-Modal Matching Applied to Stereo,
BMVC03(xx-yy).
HTML Version. 0409
BibRef

Veksler, O.,
Fast variable window for stereo correspondence using integral images,
CVPR03(I: 556-561).
IEEE DOI 0307
Speed of approach is due to the integral image technique, which allows computation of our window cost over any rectangular window in constant time, regardless of window size. BibRef

Kostousov, V.B.[Victor B.], Molochnikov, I.L.[Ilya L.],
Flexible Net Approach for Stereo Matching,
PCV02(B: 126). 0305
BibRef

Oda, K.[Kazuo], Doihara, T.[Takeshi], Shibasaki, R.[Ryosuke],
Stereo Plane Matching Technique,
PCV02(A: 228). 0305
BibRef

Xu, Y.H.[Yi-Hua], Wang, D.S.[Dong-Sheng], Feng, T.[Tao], Shum, H.Y.[Heung-Yeung],
Stereo computation using radial adaptive windows,
ICPR02(III: 595-598).
IEEE DOI 0211
BibRef

Williams, J., Bennamoun, M.,
An extended Kalman filtering approach to high precision stereo image matching,
ICIP98(II: 157-161).
IEEE DOI 9810
BibRef

Sára, R.[Radim],
Finding the Largest Unambiguous Component of Stereo Matching,
ECCV02(III: 900 ff.).
Springer DOI 0205
BibRef

Belli, T., Cord, M., and Philipp-Foliguet, S.,
Colour contribution for stereo image matching,
CCGIP00(317-322).
PS File. BibRef 0001

Chai, J.X.[Jin-Xiang], Ma, S.D.[Song-De],
An Evolutionary Framework for Stereo Correspondence,
ICPR98(Vol I: 841-844).
IEEE DOI 9808
BibRef

Mansouri, A.R., Mitiche, A., Konrad, J.,
Selective image diffusion: application to disparity estimation,
ICIP98(III: 284-288).
IEEE DOI 9810
BibRef

Pilu, M.,
A Direct Method for Stereo Correspondence Based on Singular Value Decomposition,
CVPR97(261-266).
IEEE Abstract.
IEEE DOI 9704
SVD. BibRef

Pilu, M.[Maurizio], Lorusso, A.[Adele],
Uncalibrated Stereo Correspondence by Singular Value Decomposition,
BMVC97(xx-yy).
HTML Version. 0209
BibRef

Fielding, G.[Gabriel], and Kam, M.,
Applying the Hungarian Method to Stereo Matching,
DC97(1928-1935). bipartite matching.
WWW Link. And Postscript:
PS File. BibRef 9700

Vaillant, R.[Régis], Gueguen, L.[Laurent],
Genetic algorithms applied to binocular stereovision,
ECCV94(B:193-198).
Springer DOI 9405
BibRef

Maravall, D., Fernandez, E.,
Contribution to the Matching Problem in Stereo Vision,
ICPR92(I:411-414).
IEEE DOI BibRef 9200

Yuille, A.L., and Poggio, T.A.,
A Generalized Ordering Constraint for Stereo Correspondence,
MIT AI Memo-777, May 1984. Order is important, 2 views help you see more. BibRef 8405

Takahashi, H., Tomita, F.,
Planarity Constraint in Stereo Matching,
ICPR88(I: 446-449).
IEEE DOI BibRef 8800

Dong, Y.N.[Yu-Ning], He, Z.Y.[Zhen-Ya],
A fast and effective stereo matching method-implementation aspects,
ICPR88(II: 669-671).
IEEE DOI 8811
BibRef

Blicher, A.P.[A. Peter],
Stereo Matching from the Topological Viewpoint,
DARPA83(293-297). BibRef 8300
And:
The Stereo Matching Problem from the Topological Viewpoint,
IJCAI83(1046-1049). Theory of what can happen in stereo matching?
See also Shape Representation for Computer Vision Based on Differential Topology, A. BibRef

Chapter on Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular continues in
Matching for Stereo, Occlusion, Discontinuity Analysis .