4.9.2.2 Light Field Depth Estimation

Chapter Contents (Back)
Light Field. Depth.
See also Depth of Field, Desctiptions.

Zhang, S.[Shuo], Sheng, H.[Hao], Li, C.[Chao], Zhang, J.[Jun], Xiong, Z.[Zhang],
Robust depth estimation for light field via spinning parallelogram operator,
CVIU(145), No. 1, 2016, pp. 148-159.
Elsevier DOI 1604
Light field BibRef

Cui, Z.L.[Zheng-Long], Sheng, H.[Hao], Yang, D.[Da], Wang, S.[Sizhe], Chen, R.S.[Rong-Shan], Ke, W.[Wei],
Light Field Depth Estimation for Non-Lambertian Objects via Adaptive Cross Operator,
CirSysVideo(34), No. 2, February 2024, pp. 1199-1211.
IEEE DOI 2402
Estimation, Image reconstruction, Shape, Image color analysis, Costs, Cameras, Light field, non-Lambertian, depth estimation, adaptive cross operator BibRef

Wang, W.K.[Wei-Kun], Lin, Y.F.[You-Fang], Zhang, S.[Shuo],
Enhanced Spinning Parallelogram Operator Combining Color Constraint and Histogram Integration for Robust Light Field Depth Estimation,
SPLetters(28), 2021, pp. 1080-1084.
IEEE DOI 2106
Histograms, Estimation, Image color analysis, Spinning, Noise measurement, Color, Light fields, Light field, Gaussian integration histogram BibRef

Zhang, S.[Shuo], Sheng, H.[Hao], Yang, D., Zhang, J.[Jun], Xiong, Z.[Zhang],
Micro-Lens-Based Matching for Scene Recovery in Lenslet Cameras,
IP(27), No. 3, March 2018, pp. 1060-1075.
IEEE DOI 1801
image reconstruction, image resolution, image sensors, microlenses, depth estimation method, image reconstruction, view synthesis BibRef

Tao, M.W.[Michael W.], Su, J.C., Wang, T.C.[Ting-Chun], Malik, J.[Jitendra], Ramamoorthi, R.[Ravi],
Depth Estimation and Specular Removal for Glossy Surfaces Using Point and Line Consistency with Light-Field Cameras,
PAMI(38), No. 6, June 2016, pp. 1155-1169.
IEEE DOI 1605
BibRef
Earlier: A1, A3, A4, A5, Only:
Depth Estimation for Glossy Surfaces with Light-Field Cameras,
LightField14(533-547).
Springer DOI 1504
Algorithm design and analysis. BibRef

Tao, M.W.[Michael W.], Srinivasan, P.P.[Pratul P.], Hadap, S., Rusinkiewicz, S.[Szymon], Malik, J.[Jitendra], Ramamoorthi, R.[Ravi],
Shape Estimation from Shading, Defocus, and Correspondence Using Light-Field Angular Coherence,
PAMI(39), No. 3, March 2017, pp. 546-560.
IEEE DOI 1702
BibRef
Earlier: A1, A2, A5, A4, A6, Only:
Depth from shading, defocus, and correspondence using light-field angular coherence,
CVPR15(1940-1948)
IEEE DOI 1510
Cameras BibRef

Tao, M.W.[Michael W.], Hadap, S.I.[Sun-Il], Malik, J.[Jitendra], Ramamoorthi, R.[Ravi],
Depth from Combining Defocus and Correspondence Using Light-Field Cameras,
ICCV13(673-680)
IEEE DOI 1403
BibRef

Wang, T.C.[Ting-Chun], Efros, A.A.[Alexei A.], Ramamoorthi, R.[Ravi],
Depth Estimation with Occlusion Modeling Using Light-Field Cameras,
PAMI(38), No. 11, November 2016, pp. 2170-2181.
IEEE DOI 1610
BibRef
Earlier:
Occlusion-Aware Depth Estimation Using Light-Field Cameras,
ICCV15(3487-3495)
IEEE DOI 1602
Arrays Cameras BibRef

Navarro, J., Buades, A.,
Robust and Dense Depth Estimation for Light Field Images,
IP(26), No. 4, April 2017, pp. 1873-1886.
IEEE DOI 1704
BibRef
Earlier:
Reliable light field multiwindow disparity estimation,
ICIP16(1449-1453)
IEEE DOI 1610
Algorithm design and analysis. Cameras BibRef

Zhang, Y., Lv, H., Liu, Y., Wang, H., Wang, X., Huang, Q., Xiang, X., Dai, Q.,
Light-Field Depth Estimation via Epipolar Plane Image Analysis and Locally Linear Embedding,
CirSysVideo(27), No. 4, April 2017, pp. 739-747.
IEEE DOI 1704
Cameras BibRef

Feng, M., Wang, Y., Liu, J., Zhang, L., Zaki, H.F.M., Mian, A.,
Benchmark Data Set and Method for Depth Estimation From Light Field Images,
IP(27), No. 7, July 2018, pp. 3586-3598.
IEEE DOI 1805
Cameras, Estimation, Image color analysis, Image resolution, Machine learning, Streaming media, two stream CNN BibRef

Han, Q.H.[Qi-Hui], Jung, C.[Cheolkon],
Guided filtering based data fusion for light field depth estimation with L0 gradient minimization,
JVCIR(55), 2018, pp. 449-456.
Elsevier DOI 1809
Data fusion, Guided filtering, Light field, gradient minimization, Defocus response, Occlusion, Stereo matching BibRef

Zeller, N.[Niclas], Quint, F.[Franz], Stilla, U.[Uwe],
Scale-Awareness of Light Field Camera Based Visual Odometry,
ECCV18(VIII: 732-747).
Springer DOI 1810
BibRef

Williem, Park, I.K.[In Kyu],
Cost aggregation benchmark for light field depth estimation,
JVCIR(56), 2018, pp. 38-51.
Elsevier DOI 1811
Light field, Depth estimation, Cost aggregation, Weighted rank, Benchmark BibRef

Jeon, H.G.[Hae-Gon], Park, J.[Jaesik], Choe, G.[Gyeongmin], Park, J.S.[Jin-Sun], Bok, Y.[Yunsu], Tai, Y.W.[Yu-Wing], Kweon, I.S.[In So],
Depth from a Light Field Image with Learning-Based Matching Costs,
PAMI(41), No. 2, February 2019, pp. 297-310.
IEEE DOI 1901
Cameras, Estimation, Degradation, Reliability, Training, Lenses, Computational photography, light field imaging, depth estimation, aberration correction BibRef

Kim, M.J.[Min-Jung], Oh, T.H.[Tae-Hyun], Kweon, I.S.[In So],
Cost-aware depth map estimation for Lytro camera,
ICIP14(36-40)
IEEE DOI 1502
Cameras BibRef

Huang, C.T.[Chao-Tsung],
Empirical Bayesian Light-Field Stereo Matching by Robust Pseudo Random Field Modeling,
PAMI(41), No. 3, March 2019, pp. 552-565.
IEEE DOI 1902
BibRef
Earlier:
Robust Pseudo Random Fields for Light-Field Stereo Matching,
ICCV17(11-19)
IEEE DOI 1802
Robustness, Image color analysis, Data models, Adaptation models, Bayes methods, Estimation, Markov random fields, Stereo matching, empirical Bayesian method. Bayes methods, Markov processes, expectation-maximisation algorithm, image denoising, BibRef

Zhu, K.[Kang], Xue, Y.J.[Yu-Jia], Fu, Q.[Qiang], Kang, S.B.[Sing Bing], Chen, X.L.[Xi-Lin], Yu, J.Y.[Jing-Yi],
Hyperspectral Light Field Stereo Matching,
PAMI(41), No. 5, May 2019, pp. 1131-1143.
IEEE DOI 1904
Cameras, Hyperspectral imaging, Band-pass filters, Image color analysis, Image reconstruction, spectral-aware defocus cues BibRef

Le Pendu, M., Guillemot, C., Smolic, A.,
A Fourier Disparity Layer Representation for Light Fields,
IP(28), No. 11, November 2019, pp. 5740-5753.
IEEE DOI 1909
Light fields, Apertures, Rendering (computer graphics), Calibration, Cameras, Shape, Interpolation, Light Fields, denoising BibRef

Le Pendu, M., Ozcinar, C., Smolic, A.,
Hierarchical Fourier Disparity Layer Transmission For Light Field Streaming,
ICIP20(2606-2610)
IEEE DOI 2011
Image coding, Compounds, Indexes, Image reconstruction, Binary trees, Rendering (computer graphics), Cameras, Light Fields, Streaming, Fourier Disparity Layers BibRef

Shi, J.L.[Jing-Lei], Jiang, X.R.[Xiao-Ran], Guillemot, C.[Christine],
A Framework for Learning Depth From a Flexible Subset of Dense and Sparse Light Field Views,
IP(28), No. 12, December 2019, pp. 5867-5880.
IEEE DOI 1909
Estimation, Optical imaging, Neural networks, occlusion handling BibRef

Zhou, W.H.[Wen-Hui], Zhou, E.[Enci], Liu, G.M.[Gao-Min], Lin, L.[Lili], Lumsdaine, A.[Andrew],
Unsupervised Monocular Depth Estimation From Light Field Image,
IP(29), No. , 2020, pp. 1606-1617.
IEEE DOI 1911
Estimation, Geometry, Light fields, Training, Cameras, Benchmark testing, Unsupervised learning, Light Field, multi-cue losses BibRef

Zhou, W.H.[Wen-Hui], Liu, G.[Gaomin], Shi, J.W.[Jiang-Wei], Zhang, H.[Hua], Dai, G.J.[Guo-Jun],
Depth-guided view synthesis for light field reconstruction from a single image,
IVC(95), 2020, pp. 103874.
Elsevier DOI 2004
Light field, Convolutional neural network, Depth estimation, View synthesis, View inpainting BibRef

Zhou, W.H.[Wen-Hui], Zhou, E.[Enci], Yan, Y., Lin, L.[Lili], Lumsdaine, A.[Andrew],
Learning Depth Cues from Focal Stack for Light Field Depth Estimation,
ICIP19(1074-1078)
IEEE DOI 1910
Light field, Depth estimation, Focal stack, Convolutional neural network BibRef

Liu, F., Zhou, S., Wang, Y., Hou, G., Sun, Z., Tan, T.,
Binocular Light-Field: Imaging Theory and Occlusion-Robust Depth Perception Application,
IP(29), No. , 2020, pp. 1628-1640.
IEEE DOI 1911
Imaging, Estimation, Databases, Robustness, Sun, Computational modeling, Binocular-LF imaging, occlusion robust BibRef

Ngo, T.T.[Thanh-Trung], Nagahara, H.[Hajime], Nishino, K.[Ko], Taniguchi, R.I.[Rin-Ichiro], Yagi, Y.S.[Yasu-Shi],
Reflectance and Shape Estimation with a Light Field Camera Under Natural Illumination,
IJCV(127), No. 11-12, December 2019, pp. 1707-1722.
Springer DOI 1911
BibRef

Yan, T., Jiao, J., Liu, W., Lau, R.W.H.,
Stereoscopic Image Generation From Light Field With Disparity Scaling and Super-Resolution,
IP(29), No. 1, 2020, pp. 1827-1842.
IEEE DOI 1912
Stereo image processing, Spatial resolution, Image synthesis, Cameras, super-resolution BibRef

Houben, G.[Gou], Fujita, S.[Shu], Takahashi, K.[Keita], Fujii, T.[Toshiaki],
Fast and Robust Disparity Estimation from Noisy Light Fields Using 1-D Slanted Filters,
IEICE(E102-D), No. 11, November 2019, pp. 2101-2109.
WWW Link. 1912
BibRef

Chuchvara, A., Barsi, A., Gotchev, A.,
Fast and Accurate Depth Estimation From Sparse Light Fields,
IP(29), 2020, pp. 2492-2506.
IEEE DOI 2001
3D reconstruction, depth map, light-field video, multi-view stereo (MVS), superpixel segmentation BibRef

Farhood, H.[Helia], Perry, S.[Stuart], Cheng, E.[Eva], Kim, J.[Juno],
Enhanced 3D Point Cloud from a Light Field Image,
RS(12), No. 7, 2020, pp. xx-yy.
DOI Link 2004
BibRef

Zhou, M.Y.[Ming-Yuan], Ding, Y.Q.[Yu-Qi], Ji, Y.[Yu], Young, S.S.[S. Susan], Yu, J.Y.[Jing-Yi], Ye, J.W.[Jin-Wei],
Shape and Reflectance Reconstruction Using Concentric Multi-Spectral Light Field,
PAMI(42), No. 7, July 2020, pp. 1594-1605.
IEEE DOI 2006
Cameras, Shape, Surface reconstruction, Lighting, Light sources, Image reconstruction, Computational modeling, light field BibRef

Zhang, Y., Dai, W., Xu, M., Zou, J., Zhang, X., Xiong, H.,
Depth Estimation From Light Field Using Graph-Based Structure-Aware Analysis,
CirSysVideo(30), No. 11, November 2020, pp. 4269-4283.
IEEE DOI 2011
Estimation, Spectral analysis, Light fields, Laplace equations, Correlation, Image color analysis, Cost function, Light field, graph Laplacian matrix BibRef

Jayaweera, S.S., Edussooriya, C.U.S., Wijenayake, C., Agathoklis, P., Bruton, L.T.,
Multi-Volumetric Refocusing of Light Fields,
SPLetters(28), 2021, pp. 31-35.
IEEE DOI 2101
Finite impulse response filters, Passband, Computational complexity, Cameras, Optimization, Degradation, volumetric refocusing BibRef

Denipitiyage, D.[Dishanika], Jayasundara, V.[Vinoj], Rodrigo, R.[Ranga], Edussooriya, C.U.S.[Chamira U.S.],
PointCaps: Raw point cloud processing using capsule networks with Euclidean distance routing,
JVCIR(88), 2022, pp. 103612.
Elsevier DOI 2210
Point cloud reconstruction, Classification, Capsule networks, Error routing BibRef

Li, Y., Wang, Q., Zhang, L., Lafruit, G.,
A Lightweight Depth Estimation Network for Wide-Baseline Light Fields,
IP(30), 2021, pp. 2288-2300.
IEEE DOI 2102
convolutional neural nets, feature extraction, image reconstruction, learning (artificial intelligence), synthetic dataset BibRef

Tran, T.H.[Trung-Hieu], Mammadov, G.[Gasim], Simon, S.[Sven],
GVLD: A Fast and Accurate GPU-Based Variational Light-Field Disparity Estimation Approach,
CirSysVideo(31), No. 7, July 2021, pp. 2562-2574.
IEEE DOI 2107
Estimation, Imaging, Optimization, Task analysis, Graphics processing units, Filtering, Acceleration, OpenCL BibRef

Zhang, Q.[Qi], Li, H.D.[Hong-Dong], Wang, X.[Xue], Wang, Q.[Qing],
3D Scene Reconstruction with an Un-calibrated Light Field Camera,
IJCV(129), No. 11, November 2021, pp. 3006-3026.
Springer DOI 2110
BibRef

Si, L.P.[Li-Peng], Wang, Q.[Qing],
Dense Depth-Map Estimation and Geometry Inference from Light Fields via Global Optimization,
ACCV16(III: 83-98).
Springer DOI 1704
BibRef

Jin, J.[Jing], Hou, J.H.[Jun-Hui],
Occlusion-Aware Unsupervised Learning of Depth From 4-D Light Fields,
IP(31), 2022, pp. 2216-2228.
IEEE DOI 2203
Estimation, Learning systems, Costs, Training, Geometry, Knowledge engineering, Graphics processing units, Light field, deep learning BibRef

Mehajabin, N.[Nusrat], Pourazad, M.T.[Mahsa T.], Nasiopoulos, P.[Panos],
An Efficient Pseudo-Sequence-Based Light Field Video Coding Utilizing View Similarities for Prediction Structure,
CirSysVideo(32), No. 4, April 2022, pp. 2356-2370.
IEEE DOI 2204
Cameras, Complexity theory, Lenses, Encoding, Image coding, Light fields, Microoptics, Light field video compression, HEVC, pseudo-sequence-based compression BibRef

Mehajabin, N., Luo, S.R., Yu, H.W.[H. Wei], Khoury, J., Kaur, J., Pourazad, M.T.,
An Efficient Random Access Light Field Video Compression Utilizing Diagonal Inter-View Prediction,
ICIP19(3567-3570)
IEEE DOI 1910
Light field video, random access, video compression BibRef

Zhao, Z.H.[Zhi-Hao], Cheng, S.[Samuel], Li, L.H.[Li-Hua],
Robust depth estimation on real-world light field images using Gaussian belief propagation,
IVC(122), 2022, pp. 104447.
Elsevier DOI 2205
Light field, Depth estimation, Optical flow, Real-world, Gaussian belief propagation BibRef

Iwatsuki, T.[Taisei], Takahashi, K.[Keita], Fujii, T.[Toshiaki],
Unsupervised disparity estimation from light field using plug-and-play weighted warping loss,
SP:IC(107), 2022, pp. 116764.
Elsevier DOI 2208
Light field, Disparity estimation, CNN, Unsupervised learning BibRef

Han, K.[Kang], Xiang, W.[Wei], Wang, E.[Eric], Huang, T.[Tao],
A Novel Occlusion-Aware Vote Cost for Light Field Depth Estimation,
PAMI(44), No. 11, November 2022, pp. 8022-8035.
IEEE DOI 2210
Estimation, Image edge detection, Spatial resolution, Computational modeling, Volume measurement, Visualization, vote cost BibRef

Fu, C.R.[Cong-Rui], Yuan, H.[Hui], Xu, H.J.[Hong-Ji], Zhang, H.[Hao], Shen, L.Q.[Li-Quan],
TMSO-Net: Texture adaptive multi-scale observation for light field image depth estimation,
JVCIR(90), 2023, pp. 103731.
Elsevier DOI 2301
Light field, Depth estimation, Epipolar plane image, Convolution neural network, Texture classification BibRef

Liu, Y.X.[Yu-Xuan], Aleksandrov, M.[Mitko], Hu, Z.H.[Zhi-Hua], Meng, Y.[Yan], Zhang, L.[Li], Zlatanova, S.[Sisi], Ai, H.B.[Hai-Bin], Tao, P.J.[Peng-Jie],
Accurate light field depth estimation under occlusion,
PR(138), 2023, pp. 109415.
Elsevier DOI 2303
Light field, Depth estimation, EPI, Multi-view depth maps integration, Occlusion handling BibRef

Lee, J.Y.[Jae Young], Hur, J.[Jiwan], Choi, J.[Jaehyun], Park, R.H.[Rae-Hong], Kim, J.[Junmo],
Multi-scale foreground-background separation for light field depth estimation with deep convolutional networks,
PRL(171), 2023, pp. 138-147.
Elsevier DOI 2306
Light field, Depth estimation, Foreground-Background separation BibRef

Wang, X.Z.[Xing-Zheng], Liu, J.H.[Jie-Hao], Chen, S.W.[Song-Wei], Wei, G.Y.[Guo-Yao],
Effective Light Field De-Occlusion Network Based on Swin Transformer,
CirSysVideo(33), No. 6, June 2023, pp. 2590-2599.
IEEE DOI 2306
Transformers, Feature extraction, Image restoration, Task analysis, Object detection, Convolutional neural networks, Convolution, convolutional neural network (CNN) BibRef

He, D.[Di], Liu, C.[Chang], Wu, L.[Lina], Qiu, J.[Jun],
Light Field Surface Feature and Spherical Descriptor in the Surface Scale Space,
SPLetters(30), 2023, pp. 803-807.
IEEE DOI 2307
Light fields, Feature extraction, Surface treatment, Feature detection, Laplace equations, surface scale space BibRef

Liu, D.[Deyang], Mao, Y.F.[Yi-Fan], Huang, Y.[Yan], Cao, L.Q.[Li-Qun], Wang, Y.Z.[Yuan-Zhi], Fang, Y.M.[Yu-Ming],
Optical flow-assisted multi-level fusion network for Light Field image angular reconstruction,
SP:IC(119), 2023, pp. 117031.
Elsevier DOI 2310
Light field image, Angular reconstruction, Optical flow, Multi-level fusion network BibRef

Li, P.[Peng], Zhao, J.Y.[Jia-Yin], Wu, J.Y.[Jing-Yao], Deng, C.[Chao], Han, Y.Q.[Yu-Qi], Wang, H.Q.[Hao-Qian], Yu, T.[Tao],
OPAL: Occlusion Pattern Aware Loss for Unsupervised Light Field Disparity Estimation,
PAMI(46), No. 2, February 2024, pp. 681-694.
IEEE DOI 2401
BibRef


Wang, T.[Tun], Chen, R.S.[Rong-Shan], Cong, R.X.[Rui-Xuan], Yang, D.[Da], Cui, Z.L.[Zheng-Long], Li, F.P.[Fang-Ping], Sheng, H.[Hao],
EPI-Guided Cost Construction Network for Light Field Disparity Estimation,
LightField23(3438-3446)
IEEE DOI 2309
BibRef

Yang, X.T.[Xue-Ting], Deng, J.L.[Jun-Li], Chen, R.S.[Rong-Shan], Cong, R.X.[Rui-Xuan], Ke, W.[Wei], Sheng, H.[Hao],
Disentangling Local and Global Information for Light Field Depth Estimation,
LightField23(3419-3427)
IEEE DOI 2309
BibRef

Sheng, H.[Hao], Liu, Y.B.[Ye-Bin], Yu, J.Y.[Jing-Yi], Wu, G.C.[Gao-Chang], Xiong, W.[Wei], Cong, R.X.[Rui-Xuan], Chen, R.S.[Rong-Shan], Guo, L.Z.[Long-Zhao], Xie, Y.L.[Yan-Lin], Zhang, S.[Shuo], Chang, S.[Song], Lin, Y.[Youfang], Chao, W.T.[Wen-Tao], Wang, X.[Xuechun], Wang, G.H.[Guang-Hui], Duan, F.Q.[Fu-Qing], Wang, T.[Tun], Yang, D.[Da], Cui, Z.L.[Zheng-Long], Wang, S.[Sizhe], Zhao, M.Y.[Ming-Yuan], Wang, Q.[Qiong], Chen, Q.Y.[Qian-Yu], Liang, Z.Y.[Zheng-Yu], Wang, Y.Q.[Ying-Qian], Yang, J.G.[Jun-Gang], Yang, X.T.[Xue-Ting], Deng, J.L.[Jun-Li],
LFNAT 2023 Challenge on Light Field Depth Estimation: Methods and Results,
LightField23(3473-3485)
IEEE DOI 2309
BibRef

Hur, J.[Jiwan], Lee, J.Y.[Jae Young], Choi, J.[Jaehyun], Kim, J.[Junmo],
I See-Through You: A Framework for Removing Foreground Occlusion in Both Sparse and Dense Light Field Images,
WACV23(229-238)
IEEE DOI 2302
Analytical models, Feature extraction, Cameras, Light fields, Task analysis, Image reconstruction, 3D computer vision BibRef

Han, L.[Lei], Shi, Z.[Zhan], Zheng, S.N.[Sheng-Nan], Huang, X.H.[Xiao-Hua], Xu, M.X.[Meng-Xi],
Light-Field Depth Estimation Using RNN and CRF,
ICIVC22(725-729)
IEEE DOI 2301
Human computer interaction, Recurrent neural networks, Estimation, Light fields, Convolutional neural networks, RNN BibRef

Qian, W.T.[Wen-Tong], Li, H.[Hui], Wu, Y.T.[Yun-Tao],
High-accuracy Three-dimensional Depth Measurement Using Light Field Camera via Correlation Spectrum Phase,
ICRVC22(11-15)
IEEE DOI 2301
Correlation, Phase measurement, Image resolution, Optical variables measurement, Position measurement, Cameras, high-accuracy measure BibRef

Leistner, T.[Titus], Mackowiak, R.[Radek], Ardizzone, L.[Lynton], Köthe, U.[Ullrich], Rother, C.[Carsten],
Towards Multimodal Depth Estimation from Light Fields,
CVPR22(12943-12951)
IEEE DOI 2210
Deep learning, Uncertainty, Estimation, Color, Rendering (computer graphics), Light fields, RGBD sensors and analytics BibRef

Wang, Y.Q.[Ying-Qian], Wang, L.G.[Long-Guang], Liang, Z.Y.[Zheng-Yu], Yang, J.G.[Jun-Gang], An, W.[Wei], Guo, Y.L.[Yu-Lan],
Occlusion-Aware Cost Constructor for Light Field Depth Estimation,
CVPR22(19777-19786)
IEEE DOI 2210
Deep learning, Costs, Estimation, Mean square error methods, Benchmark testing, Light fields, Computational photography, 3D from multi-view and sensors BibRef

Lourenco, R.[Rui], Rivero-Castillo, D.[Daniel], Thomaz, L.A.[Lucas A.], Assuncao, P.A.A.[Pedro A. A.], Tavora, L.M.N.[Luis M.N.], de Faria, S.M.M.[Sergio M. M.],
4D Light Field Disparity Map estimation using Krawtchouk Polynomials,
IPTA20(1-6)
IEEE DOI 2206
Human computer interaction, Visualization, Tensors, Image edge detection, Estimation, Tools, Light fields, Light Field, Structure Tensor BibRef

Zhu, C.J.[Chang-Jian], Zhang, H.[Hong], Wei, Y.[Ying], He, N.[Nan], Liu, Q.M.[Qiu-Ming],
An Iterative Correction Phase of Light Field for Novel View Reconstruction,
MMMod22(II:62-72).
Springer DOI 2203
BibRef

Huang, Z.C.[Zhi-Cong], Hu, X.M.[Xue-Mei], Xue, Z.[Zhou], Xu, W.Z.[Wei-Zhu], Yue, T.[Tao],
Fast Light-field Disparity Estimation with Multi-disparity-scale Cost Aggregation,
ICCV21(6300-6309)
IEEE DOI 2203
Solid modeling, Costs, Codes, Computational modeling, Memory management, Estimation, Stereo, Optimization and learning methods BibRef

Guo, M.[Mantang], Jin, J.[Jing], Liu, H.[Hui], Hou, J.H.[Jun-Hui],
Learning Dynamic Interpolation for Extremely Sparse Light Fields with Wide Baselines,
ICCV21(2430-2439)
IEEE DOI 2203
Geometry, Learning systems, Interpolation, Correlation, Codes, Computational modeling, Computational photography, Image and video synthesis BibRef

Ma, D.[Dizhi], Lumsdaine, A.[Andrew],
Fast and Efficient Neural Network for Light Field Disparity Estimation,
ICPR21(2920-2926)
IEEE DOI 2105
Performance evaluation, Runtime, Computational modeling, Neural networks, Estimation, Imaging, Machine learning BibRef

Cardoso, J.L.[João L.], Gonçalves, N.[Nuno], Wimmer, M.[Michael],
Cost Volume Refinement for Depth Prediction,
ICPR21(354-361)
IEEE DOI 2105
Light-Field camera. Smoothing methods, Volume measurement, Refining, Redundancy, Pipelines, Cameras, Cost-Volumes BibRef

Duong, V.V., Huu, T.N., Jeon, B.,
Robust Light Field Depth Estimation With Occlusion Based On Spatial And Spectral Entropies Data Costs,
ICIP20(2631-2635)
IEEE DOI 2011
Light field, depth estimation, occlusion, spatial entropy, spectral entropy BibRef

Cunha, F., Thomaz, L.A., Tavora, L.M.N., Assunção, P.A.A., Fonseca-Pinto, R., Faria, S.M.M.,
Robust Depth Estimation From Multi-Focus Plenoptic Images,
ICIP20(2626-2630)
IEEE DOI 2011
Lenses, Estimation, Image edge detection, Cameras, Robustness, Quantization (signal), Indexes, Light Field, Depth Estimation, Lenslet BibRef

Shi, J., Jiang, X., Guillemot, C.,
Learning Fused Pixel and Feature-Based View Reconstructions for Light Fields,
CVPR20(2552-2561)
IEEE DOI 2008
Image reconstruction, Feature extraction, Interpolation, Estimation, Rendering (computer graphics), Spatial resolution, Image color analysis BibRef

Nousias, S., Lourakis, M., Keane, P., Ourselin, S., Bergeles, C.[Christos],
A Linear Approach to Absolute Pose Estimation for Light Fields,
3DV20(672-681)
IEEE DOI 2102
Cameras, Light fields, Pose estimation, Image reconstruction, Pipelines, Lenses BibRef

Nousias, S.[Sotiris], Lourakis, M.[Manolis], Bergeles, C.[Christos],
Large-Scale, Metric Structure From Motion for Unordered Light Fields,
CVPR19(3287-3296).
IEEE DOI 2002
BibRef

Leistner, T., Schilling, H., Mackowiak, R., Gumhold, S., Rother, C.,
Learning to Think Outside the Box: Wide-Baseline Light Field Depth Estimation with EPI-Shift,
3DV19(249-257)
IEEE DOI 1911
Cameras, Estimation, Light fields, Training data, Benchmark testing, Deep learning, depth estimation, computer vision BibRef

Schilling, H., Diebold, M., Rother, C., Jähne, B.,
Trust your Model: Light Field Depth Estimation with Inline Occlusion Handling,
CVPR18(4530-4538)
IEEE DOI 1812
Cost function, Estimation, Surface reconstruction, Cameras, Image reconstruction, Robustness BibRef

Darwish, W., Bolsee, Q., Munteanu, A.,
Plenoptic Camera Calibration Based on Sub-Aperture Images,
ICIP19(3527-3531)
IEEE DOI 1910
light fields, calibration, camera arrays BibRef

Fujigaki, S., Kodama, K., Hamamoto, T.,
Multi-View Imaging System Using Paraboloidal Mirror Arrays for Efficient Acquisition of Dynamic Light Fields,
ICIP19(3532-3536)
IEEE DOI 1910
light field, multi-view, acquisition, mirror, paraboloid BibRef

Pan, X., Zhang, T., Wang, H.,
A Method for Handling Multi-Occlusion in Depth Estimation of Light Field,
ICIP19(1069-1073)
IEEE DOI 1910
Depth estimation, light field, occlusion edges, handling multi-occlusion BibRef

Ghorai, M., Munteanu, A.,
Depth Estimation with Occlusion Prediction in Light Field Images,
ICIP19(1049-1053)
IEEE DOI 1910
Light fields, depth estimation, occlusion BibRef

Wang, Y., Zhang, X., Li, H., Ming, A.,
Real-Time Light Field Depth Estimation via GPU-Accelerated Muti-View Semi-Global Matching,
ICIP19(1054-1058)
IEEE DOI 1910
light-field, depth estimation, GPU, real-time, multi-view stereo BibRef

Stacey, A.[Adam], Maddern, W.[Will], Singh, S.[Surya],
Fast Light Field Disparity Estimation via a Parallel Filtered Cost Volume Approach,
ACCV18(II:256-268).
Springer DOI 1906
BibRef

Ivan, A.[Andre], Unknown, W.[Williem], Park, I.K.[In Kyu],
Light Field Depth Estimation on Off-the-Shelf Mobile GPU,
ECVW18(747-74709)
IEEE DOI 1812
Graphics processing units, Estimation, Histograms, Entropy, Instruction sets, Kernel, Memory management BibRef

Zhou, W., Liang, L., Zhang, H., Lumsdaine, A., Lin, L.,
Scale and Orientation Aware EPI-Patch Learning for Light Field Depth Estimation,
ICPR18(2362-2367)
IEEE DOI 1812
Estimation, Feature extraction, Benchmark testing, Adaptation models, Adaptive systems, Visualization BibRef

Rogge, S., Munteanu, A.,
Depth Estimation in Light Field Camera Arrays Based on Multi-Stereo Matching and Belief Propagation,
3DTV-CON18(1-4)
IEEE DOI 1812
belief networks, cameras, image matching, stereo image processing, singular light field cameras, belief propagation BibRef

Peng, J., Xiong, Z., Liu, D., Chen, X.,
Unsupervised Depth Estimation from Light Field Using a Convolutional Neural Network,
3DV18(295-303)
IEEE DOI 1812
feature extraction, image matching, image reconstruction, image resolution, image segmentation, image sensors, Unsupervised Learning BibRef

David, P., Le Pendu, M., Guillemot, C.,
Sparse to Dense Scene Flow Estimation From Light Fields,
ICIP19(3736-3740)
IEEE DOI 1910
Scene flow, optical flow, light field, sparse to dense BibRef

Jiang, X., Le Pendu, M., Guillemot, C.,
Depth Estimation with Occlusion Handling from a Sparse Set of Light Field Views,
ICIP18(634-638)
IEEE DOI 1809
Estimation, Optical imaging, Integrated optics, Image color analysis, Optical filters, Reliability, low rank approximation BibRef

Houben, G., Fujita, S., Takahashi, K., Fujii, T.,
Fast and Robust Disparity Estimation for Noisy Light Fields,
ICIP18(2610-2614)
IEEE DOI 1809
Noise reduction, Estimation, Noise measurement, Kernel, Robustness, Tensile stress, Noise level, Light field, Epipolar plane image, Disparity BibRef

Wang, P., Jin, X., Li, C., Chen, Y., Dai, Q.,
Light Field Stitching for Parallax Tolerance,
ICIP18(2585-2589)
IEEE DOI 1809
Cameras, Filtering, Feature extraction, Estimation, Visualization, Optical distortion, LF stitching, parallax tolerance BibRef

Lourenco, R., Assuncao, P.A.A., Tavora, L.M.N., Fonseca-Pinto, R., Faria, S.M.M.,
Silhouette Enhancement in Light Field Disparity Estimation Using the Structure Tensor,
ICIP18(2580-2584)
IEEE DOI 1809
Estimation, Image edge detection, Reliability, Tensile stress, Visualization, structure tensor BibRef

Palmieri, L., Koch, R., Het Veld, R.O.,
The Plenoptic 2.0 Toolbox: Benchmarking of Depth Estimation Methods for MLA-Based Focused Plenoptic Cameras,
ICIP18(649-653)
IEEE DOI 1809
Cameras, Estimation, Benchmark testing, Visualization, Measurement uncertainty, Open source software, Tools, Lightfield, MLA (Micro-lens Array) BibRef

Gava, C.C., Stricker, D., Yokota, S.,
Dense Scene Reconstruction from Spherical Light Fields,
ICIP18(4178-4182)
IEEE DOI 1809
Image reconstruction, Cameras, Distortion, Approximation algorithms, Surface reconstruction, light fields BibRef

Peng, J., Xiong, Z., Zhang, Y., Liu, D., Wu, F.,
LF-fusion: Dense and accurate 3D reconstruction from light field images,
VCIP17(1-4)
IEEE DOI 1804
image fusion, image reconstruction, iterative methods, Kinect-fusion, LF images, LF-fusion, depth estimation, depth maps, point cloud BibRef

Li, Y., Lafruit, G.,
Robust disparity estimation on sparse sampled light field images,
3DTV-CON17(1-4)
IEEE DOI 1804
image colour analysis, image matching, image reconstruction, stereo image processing, Epipolar-Plane Image analysis, Radiometric changes BibRef

Johannsen, O., Honauer, K., Goldluecke, B., Alperovich, A., Battisti, F., Bok, Y., Brizzi, M., Carli, M., Choe, G., Diebold, M., Gutsche, M., Jeon, H.G., Kweon, I.S., Park, J., Park, J., Schilling, H., Sheng, H., Si, L., Strecke, M., Sulc, A., Tai, Y.W., Wang, Q., Wang, T.C., Wanner, S., Xiong, Z., Yu, J., Zhang, S., Zhu, H.,
A Taxonomy and Evaluation of Dense Light Field Depth Estimation Algorithms,
LightField17(1795-1812)
IEEE DOI 1709
Benchmark testing, Cameras, Estimation, Measurement, Taxonomy, Three-dimensional, displays BibRef

Zhou, W.H.[Wen-Hui], Li, P., Lumsdaine, A., Lin, L.[Lili],
Light-field flow: A subpixel-accuracy depth flow estimation with geometric occlusion model from a single light-field image,
ICIP17(1632-1636)
IEEE DOI 1803
Adaptive optics, Cameras, Estimation, Geometrical optics, Optical imaging, Optical sensors, Robustness, depth estimation, subpixel accuracy BibRef

Zhou, W.H.[Wen-Hui], Lumsdaine, A., Lin, L.[Lili],
Depth estimation with cascade occlusion culling filter for light-field cameras,
ICPR16(1887-1892)
IEEE DOI 1705
Cameras, Estimation, Image edge detection, Mathematical model, Optimization, Surface, texture BibRef

Honauer, K.[Katrin], Johannsen, O.[Ole], Kondermann, D.[Daniel], Goldluecke, B.[Bastian],
A Dataset and Evaluation Methodology for Depth Estimation on 4D Light Fields,
ACCV16(III: 19-34).
Springer DOI 1704
BibRef

Paramonov, V.[Vladimir], Panchenko, I.[Ivan], Bucha, V.[Victor], Drogolyub, A.[Andrey], Zagoruyko, S.[Sergey],
Depth Camera Based on Color-Coded Aperture,
CCD16(910-918)
IEEE DOI 1612
Single lens, passive. BibRef

Williem, W., Park, I.K.[In Kyu], Lee, K.M.[Kyoung Mu],
Robust Light Field Depth Estimation Using Occlusion-Noise Aware Data Costs,
PAMI(40), No. 10, October 2018, pp. 2484-2497.
IEEE DOI 1809
Estimation, Robustness, Entropy, Image color analysis, Cameras, Optimization methods, Light field, depth estimation, constrained adaptive defocus BibRef

Williem, W., Park, I.K.[In Kyu],
Robust Light Field Depth Estimation for Noisy Scene with Occlusion,
CVPR16(4396-4404)
IEEE DOI 1612
BibRef

Sajjadi, M.S.M.[Mehdi S. M.], Köhler, R.[Rolf], Schölkopf, B.[Bernhard], Hirsch, M.[Michael],
Depth Estimation Through a Generative Model of Light Field Synthesis,
GCPR16(426-438).
Springer DOI 1611
BibRef

Johannsen, O.[Ole], Sulc, A.[Antonin], Marniok, N.[Nico], Goldluecke, B.[Bastian],
Layered Scene Reconstruction from Multiple Light Field Camera Views,
ACCV16(III: 3-18).
Springer DOI 1704
BibRef
And: A1, A2, A4, Only:
What Sparse Light Field Coding Reveals about Scene Structure,
CVPR16(3262-3270)
IEEE DOI 1612
BibRef
And: A1, A2, A4, Only:
Occlusion-Aware Depth Estimation Using Sparse Light Field Coding,
GCPR16(207-218).
Springer DOI 1611
BibRef
Earlier: A1, A2, A4, Only:
On Linear Structure from Motion for Light Field Cameras,
ICCV15(720-728)
IEEE DOI 1602
Calibration BibRef

Donne, S.[Simon], Goossens, B.[Bart], Aelterman, J.[Jan], Philips, W.[Wilfried],
Variational multi-image stereo matching,
ICIP15(897-901)
IEEE DOI 1512
depth estimation, light field, stereo BibRef

Vasko, R.[Ross], Zeller, N.[Niclas], Quint, F.[Franz], Stilla, U.[Uwe],
A Real-Time Depth Estimation Approach for a Focused Plenoptic Camera,
ISVC15(II: 70-80).
Springer DOI 1601
BibRef

Xu, Y.T.[Ya-Tong], Jin, X.[Xin], Dai, Q.H.[Qiong-Hai],
Depth estimation by analyzing intensity distribution for light-field cameras,
ICIP15(3540-3544)
IEEE DOI 1512
Light-field, confidence measure, depth estimation, intensity range BibRef

Kim, C.I.[Chang-Il], Subr, K.[Kartic], Mitchell, K.[Kenny], Sorkine-Hornung, A.[Alexander], Gross, M.[Markus],
Online view sampling for estimating depth from light fields,
ICIP15(1155-1159)
IEEE DOI 1512
BibRef

Kopf, C.[Christian], Pock, T.[Thomas], Blaschitz, B.[Bernhard], Štolc, S.[Svorad],
Inline Double Layer Depth Estimation with Transparent Materials,
GCPR20(418-431).
Springer DOI 2110
BibRef

Antensteiner, D.[Doris], Štolc, S.[Svorad], Huber-Mörk, R.[Reinhold],
Depth Estimation with Light Field and Photometric Stereo Data Using Energy Minimization,
CIARP16(175-183).
Springer DOI 1703
BibRef

Soukup, D., Huber-Mörk, R.[Reinhold], Štolc, S.[Svorad], Holländer, B.,
Depth Estimation within a Multi-Line-Scan Light-Field Framework,
ISVC14(II: 471-481).
Springer DOI 1501
BibRef

Tosic, I.[Ivana], Berkner, K.[Kathrin],
3D keypoint detection by light field scale-depth space analysis,
ICIP14(1927-1931)
IEEE DOI 1502
BibRef
And:
Light Field Scale-Depth Space Transform for Dense Depth Estimation,
CCD14(441-448)
IEEE DOI 1409
Cameras BibRef

Chapter on Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar continues in
Complex Log Mapping, Algorithms and Sensors .


Last update:Mar 16, 2024 at 20:36:19