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
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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
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Zhang, S.[Shuo],
Sheng, H.[Hao],
Yang, D.,
Zhang, J.[Jun],
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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
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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
Zhang, S.[Shansi],
Meng, N.[Nan],
Lam, E.Y.[Edmund Y.],
Unsupervised Light Field Depth Estimation via Multi-View Feature
Matching With Occlusion Prediction,
CirSysVideo(34), No. 4, April 2024, pp. 2261-2273.
IEEE DOI
2404
Estimation, Costs, Training, Image edge detection,
Feature extraction, Convolutional neural networks, Training data,
occlusion prediction
BibRef
Yan, W.B.[Wen-Bin],
Zhang, X.G.[Xiao-Gang],
Chen, H.[Hua],
Occlusion-Aware Unsupervised Light Field Depth Estimation Based on
Multi-Scale GANs,
CirSysVideo(34), No. 7, July 2024, pp. 6318-6333.
IEEE DOI
2407
Estimation, Light fields, Learning systems,
Generative adversarial networks, Task analysis, attention modulel
BibRef
Cui, Z.L.[Zheng-Long],
Yang, D.[Da],
Sheng, H.[Hao],
Wang, S.[Sizhe],
Chen, R.S.[Rong-Shan],
Cong, R.X.[Rui-Xuan],
Ke, W.[Wei],
Triple Consistency for Transparent Cheating Problem in Light Field
Depth Estimation,
MultMed(26), 2024, pp. 10651-10664.
IEEE DOI
2411
Estimation, Image reconstruction, Costs, Tensors, Mirrors, Cameras,
Lighting, Light field, non-lambertian, depth estimation,
triple consistency
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 .