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
Akhavan, T.[Tara],
Kaufmann, H.[Hannes],
Backward compatible HDR stereo matching:
A hybrid tone-mapping-based framework,
JIVP(2015), No. 1, 2015, pp. 36.
DOI Link
1512
BibRef
Huang, X.M.[Xiao-Ming],
Zhang, Y.J.[Yu-Jin],
An O(1) disparity refinement method for stereo matching,
PR(55), No. 1, 2016, pp. 198-206.
Elsevier DOI
1604
Stereo matching
BibRef
Huang, X.M.[Xiao-Ming],
Cui, G.Q.[Guo-Qin],
Zhang, Y.D.[Yun-Dong],
A fast non-local disparity refinement method for stereo matching,
ICIP14(3823-3827)
IEEE DOI
1502
Accuracy
BibRef
Fu, L.,
Peng, G.,
Song, W.,
Histogram-based cost aggregation strategy with joint bilateral
filtering for stereo matching,
IET-CV(10), No. 3, 2016, pp. 173-181.
DOI Link
1604
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.
WWW Link.
1604
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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 .