11.14.3.9.8 Inpainting, Video Inpainting

Patwardhan, K.A., Sapiro, G., Bertalmio, M.,
Video Inpainting Under Constrained Camera Motion,
IP(16), No. 2, February 2007, pp. 545-553.
IEEE DOI 0702
BibRef

Patwardhan, K.A., Sapiro, G.,
Projection based image and video inpainting using wavelets,
ICIP03(I: 857-860).
IEEE DOI 0312
BibRef

Bertalmío, M., Bertozzi, A.L., Sapiro, G.,
Navier-Stokes, Fluid Dynamics, and Image and Video Inpainting,
CVPR01(I:355-362).
IEEE DOI 0110
Fill part of an image from the surround. Especially with large magnifications. BibRef

Jia, J.Y.[Jia-Ya], Tai, Y.W.[Yu-Wing], Wu, T.P.[Tai-Pang], Tang, C.K.[Chi-Keung],
Video Repairing under Variable Illumination Using Cyclic Motions,
PAMI(28), No. 5, May 2006, pp. 832-839.
IEEE DOI 0604
Synthensize pixels missing in video. User assisted video layer segmentation, then automatic repair.
See also Inference of Segmented Color and Texture Description by Tensor Voting. BibRef

Venkatesh, M.V.[M. Vijay], Cheung, S.C.S.[Sen-Ching Samson], Zhao, J.[Jian],
Efficient Object-Based Video Inpainting,
PRL(30), No. 2, 15 January 2009, pp. 168-179.
Elsevier DOI 0804
BibRef
Earlier: A2, A3, A1: ICIP06(705-708).
IEEE DOI 0610
Video inpainting; Sliding window; Template matching; Dynamic programming; Background replacement; Object segmentation BibRef

Shih, T.K.[Timothy K.], Tang, N.C., Hwang, J.N.,
Exemplar-Based Video Inpainting Without Ghost Shadow Artifacts by Maintaining Temporal Continuity,
CirSysVideo(19), No. 3, March 2009, pp. 347-360.
IEEE DOI 0903
BibRef

Shih, T.K.[Timothy K.], Tan, N.C.[Nick C.], Tsai, J.C.[Joseph C.], Zhong, H.Y.[Hsing-Ying],
Video falsifying by motion interpolation and inpainting,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Tsai, T.H., Fang, C.L.,
Text-Video Completion Using Structure Repair and Texture Propagation,
MultMed(13), No. 1, 2011, pp. 29-39.
IEEE DOI 1102
BibRef

Ling, C.H.[Chih-Hung], Lin, C.W.[Chia-Wen], Su, C.W.[Chih-Wen], Chen, Y.S.[Yong-Sheng], Liao, H.Y.M.[Hong-Yuan Mark],
Virtual Contour Guided Video Object Inpainting Using Posture Mapping and Retrieval,
MultMed(13), No. 2, 2011, pp. 292-302.
IEEE DOI 1103
BibRef
Earlier: A1, A2, A3, A5, A4:
Video object inpainting using posture mapping,
ICIP09(2785-2788).
IEEE DOI 0911
BibRef

Ling, C.H.[Chih-Hung], Liang, Y.M.[Yu-Ming], Lin, C.W.[Chia-Wen], Chen, Y.S.[Yong-Sheng], Liao, H.Y.M.[Hong-Yuan Mark],
Human Object Inpainting Using Manifold Learning-Based Posture Sequence Estimation,
IP(20), No. 11, November 2011, pp. 3124-3135.
IEEE DOI 1110
BibRef
Earlier:
Video object inpainting using manifold-based action prediction,
ICIP10(425-428).
IEEE DOI 1009
Human posture, graphical model, posture sequence estimation. BibRef

Tang, N.C., Hsu, C.T.[Chiou-Ting], Su, C.W.[Chih-Wen], Shih, T.K., Liao, H.Y.M.,
Video Inpainting on Digitized Vintage Films via Maintaining Spatiotemporal Continuity,
MultMed(13), No. 4, 2011, pp. 602-614.
IEEE DOI 1108
BibRef

Xiong, H., Xu, Y., Zheng, Y.F., Chen, C.W.,
Priority Belief Propagation-Based Inpainting Prediction With Tensor Voting Projected Structure in Video Compression,
CirSysVideo(21), No. 8, August 2011, pp. 1115-1129.
IEEE DOI 1108
BibRef

Mosleh, A., Bouguila, N., Ben Hamza, A.,
Video Completion Using Bandlet Transform,
MultMed(14), No. 6, 2012, pp. 1591-1601.
IEEE DOI 1212

See also Automatic Inpainting Scheme for Video Text Detection and Removal. BibRef

Favorskaya, M.[Margarita], Damov, M.[Mikhail], Zotin, A.[Alexander],
Accurate spatio-temporal reconstruction of missing data in dynamic scenes,
PRL(34), No. 14, 2013, pp. 1694-1700.
Elsevier DOI 1308
Image inpainting BibRef

Wang, M.H.[Miao-Hui], Yan, B.[Bo], Ngan, K.N.[King Ngi],
An efficient framework for image/video inpainting,
SP:IC(28), No. 7, 2013, pp. 753-762.
Elsevier DOI 1307
Image inpainting BibRef

Wang, M.H.[Miao-Hui], Yan, B.[Bo], Gharavi, H.[Hamid],
Pyramid model based Down-sampling for image inpainting,
ICIP10(429-432).
IEEE DOI 1009
BibRef

Mosleh, A.[Ali], Bouguila, N.[Nizar], Ben Hamza, A.,
Bandlet-based sparsity regularization in video inpainting,
JVCIR(25), No. 5, 2014, pp. 855-863.
Elsevier DOI 1406
Bandlets
See also Image and video spatial super-resolution via bandlet-based sparsity regularization and structure tensor. BibRef

Graja, O.[Omar], Najar, F.[Fatma], Bouguila, N.[Nizar],
Generalized Inverted Dirichlet Optimal Predictor for Image Inpainting,
ISVC20(I:410-421).
Springer DOI 2103
BibRef

Newson, A.[Alasdair], Almansa, A.[Andrés], Fradet, M., Gousseau, Y.[Yann], Pérez, P.[Patrick],
Video Inpainting of Complex Scenes,
SIIMS(7), No. 4, 2014, pp. 1993-2019.
DOI Link 1402
BibRef

Newson, A.[Alasdair], Almansa, A.[Andrés], Gousseau, Y.[Yann], Pérez, P.[Patrick],
Non-Local Patch-Based Image Inpainting,
IPOL(7), 2017, pp. 373-385.
DOI Link 1801
BibRef

Ebdelli, M., Le Meur, O., Guillemot, C.,
Video Inpainting With Short-Term Windows: Application to Object Removal and Error Concealment,
IP(24), No. 10, October 2015, pp. 3034-3047.
IEEE DOI 1507
Cameras BibRef

Gao, Y., Cheung, G.[Gene], Maugey, T.[Thomas], Frossard, P.[Pascal], Liang, J.,
Encoder-Driven Inpainting Strategy in Multiview Video Compression,
IP(25), No. 1, January 2016, pp. 134-149.
IEEE DOI 1601
Artificial intelligence BibRef

Maugey, T.[Thomas], Frossard, P.[Pascal], Cheung, G.[Gene],
Consistent view synthesis in interactive multiview imaging,
ICIP12(2717-2720).
IEEE DOI 1302
BibRef

Daribo, I.[Ismael], Cheung, G.[Gene], Maugey, T.[Thomas], Frossard, P.[Pascal],
R-D optimized auxiliary information for inpainting-based view synthesis,
3DTV12(1-4).
IEEE DOI 1212
BibRef

Farid, M.S.[Muhammad Shahid], Mahmood, A.[Arif], Grangetto, M.[Marco],
Image de-fencing framework with hybrid inpainting algorithm,
SIViP(10), No. 7, October 2016, pp. 1193-1201.
WWW Link. 1609
BibRef

Farid, M.S.[Muhammad Shahid], Lucenteforte, M.[Maurizio], Grangetto, M.[Marco],
Edge enhancement of depth based rendered images,
ICIP14(5452-5456)
IEEE DOI 1502
Cameras BibRef

Farid, M.S.[Muhammad Shahid], Lucenteforte, M.[Maurizio], Grangetto, M.[Marco],
A panoramic 3D video coding with directional depth aided inpainting,
ICIP14(3233-3237)
IEEE DOI 1502
Cameras BibRef

Paradiso, V.[Vincenzo], Lucenteforte, M.[Maurizio], Grangetto, M.[Marco],
A novel interpolation method for 3D view synthesis,
3DTV12(1-4).
IEEE DOI 1212
BibRef

Xu, Z., Zhang, Q., Cao, Z., Xiao, C.,
Video Background Completion Using Motion-Guided Pixel Assignment Optimization,
CirSysVideo(26), No. 8, August 2016, pp. 1393-1406.
IEEE DOI 1609
Markov processes BibRef

Kim, H.G.[Hak Gu], Ro, Y.M.[Yong Man],
Multiview Stereoscopic Video Hole Filling Considering Spatiotemporal Consistency and Binocular Symmetry for Synthesized 3D Video,
CirSysVideo(27), No. 7, July 2017, pp. 1435-1449.
IEEE DOI 1707
Color, Filling, Image color analysis, Optimization, Stereo image processing, Visualization, Binocular symmetry, hole filling, synthesized 3D video, temporal consistency, visual, discomfort BibRef

Kim, H.G.[Hak Gu], Yoon, S.S.[Soo Sung], Ro, Y.M.[Yong Man],
Temporally consistent hole filling method based on global optimization with label propagation for 3D video,
ICIP15(3136-3140)
IEEE DOI 1512
3D video BibRef

Bokov, A.[Alexander], Vatolin, D.[Dmitriy], Erofeev, M.[Mikhail], Gitman, Y.[Yury],
Toward an objective benchmark for video completion,
SIViP(13), No. 3, April 2019, pp. 601-608.
Springer DOI 1904
BibRef

Szeto, R.[Ryan], Sun, X.M.[Xi-Meng], Lu, K.Y.[Kun-Yi], Corso, J.J.[Jason J.],
A Temporally-Aware Interpolation Network for Video Frame Inpainting,
PAMI(42), No. 5, May 2020, pp. 1053-1068.
IEEE DOI 2004
BibRef
Earlier: A2, A1, A4, Only: ACCV18(III:249-264).
Springer DOI 1906
Interpolation, Task analysis, Predictive models, Data models, Sun, Video inpainting, video prediction, temporal upsampling BibRef

Kim, D.[Dahun], Woo, S.[Sanghyun], Lee, J.Y.[Joon-Young], Kweon, I.S.[In So],
Recurrent Temporal Aggregation Framework for Deep Video Inpainting,
PAMI(42), No. 5, May 2020, pp. 1038-1052.
IEEE DOI 2004
Code, Inpainting.
WWW Link.
WWW Link. Video inpainting, video completion, video object removal, video caption removal, video decaptioning, video editing BibRef

Gao, C.[Chen], Saraf, A.[Ayush], Huang, J.B.[Jia-Bin], Kopf, J.[Johannes],
Flow-edge Guided Video Completion,
ECCV20(XII: 713-729).
Springer DOI 2010
BibRef

Wu, Z.L.[Zhi-Liang], Zhang, K.[Kang], Xuan, H.Y.[Han-Yu], Yang, J.[Jian], Yan, Y.[Yan],
DAPC-Net: Deformable Alignment and Pyramid Context Completion Networks for Video Inpainting,
SPLetters(28), 2021, pp. 1145-1149.
IEEE DOI 2106
Convolution, Visualization, Semantics, Redundancy, Coherence, Task analysis, Decoding, Video inpainting, pyramid-context completion BibRef

Zarif, S.[Sameh], Ibrahim, M.[Mina],
Video Inpainting: A Complete Framework,
IJIG(21), No. 3, July 2021, pp. 2150038.
DOI Link 2107
BibRef

Hara, Y.[Yusuke], Wang, X.T.[Xue-Ting], Yamasaki, T.[Toshihiko],
Video Inpainting by Frame Alignment with Deformable Convolution,
IEICE(E104-D), No. 8, August 2021, pp. 1349-1358.
WWW Link. 2108
BibRef

Wang, C.Q.[Chao-Qun], Chen, X.J.[Xue-Jin], Min, S.B.[Shao-Bo], Wang, J.P.[Jia-Ping], Zha, Z.J.[Zheng-Jun],
Structure-Guided Deep Video Inpainting,
CirSysVideo(31), No. 8, August 2021, pp. 2953-2965.
IEEE DOI 2108
Coherence, Image edge detection, Visualization, Correlation, Optical imaging, Image color analysis, flow assistance BibRef

Liu, R.X.[Rui-Xin], Li, B.[Bairong], Zhu, Y.S.[Yue-Sheng],
Temporal Group Fusion Network for Deep Video Inpainting,
CirSysVideo(32), No. 6, June 2022, pp. 3539-3551.
IEEE DOI 2206
Task analysis, Convolution, Visualization, Video sequences, Image restoration, Streaming media, Video inpainting, video editing BibRef

Jia, Z.G.[Zhi-Gang], Jin, Q.Y.[Qi-Yu], Ng, M.K.[Michael K.], Zhao, X.L.[Xi-Le],
Non-Local Robust Quaternion Matrix Completion for Large-Scale Color Image and Video Inpainting,
IP(31), 2022, pp. 3868-3883.
IEEE DOI 2206
Quaternions, Color, Image color analysis, Image reconstruction, Tensors, Sparse matrices, Low-rank approximation, color video BibRef

Chen, J.[Junren], Ng, M.K.[Michael K.],
Color Image Inpainting via Robust Pure Quaternion Matrix Completion: Error Bound and Weighted Loss,
SIIMS(15), No. 3, 2022, pp. 1469-1498.
DOI Link 2209
BibRef

Wang, J.Q.[Jia-Qi], Chen, K.[Kai], Xu, R.[Rui], Liu, Z.W.[Zi-Wei], Loy, C.C.[Chen Change], Lin, D.[Dahua],
CARAFE++: Unified Content-Aware ReAssembly of FEatures,
PAMI(44), No. 9, September 2022, pp. 4674-4687.
IEEE DOI 2208
Kernel, Task analysis, Image segmentation, Semantics, Interpolation, Convolution, Object detection, Feature reassembly, image inpainting BibRef

Xu, R.[Rui], Li, X.X.[Xiao-Xiao], Zhou, B.L.[Bo-Lei], Loy, C.C.[Chen Change],
Deep Flow-Guided Video Inpainting,
CVPR19(3718-3727).
IEEE DOI 2002
BibRef

Kim, J.[Jihoon], Byun, T.[Taehyun], Shin, S.[Seungyoun], Won, J.[Jungdam], Choi, S.[Sungjoon],
Conditional motion in-betweening,
PR(132), 2022, pp. 108894.
Elsevier DOI 2209
Motion in-betweening, Conditional motion generation, Generative model, Motion data augmentation BibRef

Hu, C.B.[Chuan-Bo], Jia, S.[Shan], Zhang, F.[Fan], Li, X.[Xin],
A saliency-guided street view image inpainting framework for efficient last-meters wayfinding,
PandRS(195), 2023, pp. 365-379.
Elsevier DOI 2301
Street-level image, Saliency-guided image inpainting, Image-based wayfinding, Image segmentation BibRef

Ye, X.[Xi], Bilodeau, G.A.[Guillaume-Alexandre],
Video prediction by efficient transformers,
IVC(130), 2023, pp. 104612.
Elsevier DOI 2301
Video prediction, Transformers, Video representation learning, Autoregressive generative models, Non-autoregressive generative models BibRef

Tudavekar, G.[Gajanan], Saraf, S.S.[Santosh S.], Patil, S.R.[Sanjay R.],
Spatio-Temporal Inference Transformer Network for Video Inpainting,
IJIG(23), No. 1 2023, pp. 2350007.
DOI Link 2302
BibRef

Ji, Z.[Zhong], Hou, J.C.[Jia-Cheng], Su, Y.[Yimu], Pang, Y.W.[Yan-Wei], Li, X.L.[Xue-Long],
G2LP-Net: Global to Local Progressive Video Inpainting Network,
CirSysVideo(33), No. 3, March 2023, pp. 1082-1092.
IEEE DOI 2303
Convolution, Wires, Optical imaging, Feature extraction, Task analysis, Optical fiber networks, Video inpainting, self-attention BibRef

Wu, Z.L.[Zhi-Liang], Sun, C.C.[Chang-Chang], Xuan, H.Y.[Han-Yu], Zhang, K.[Kang], Yan, Y.[Yan],
Divide-and-Conquer Completion Network for Video Inpainting,
CirSysVideo(33), No. 6, June 2023, pp. 2753-2766.
IEEE DOI 2306
Discrete wavelet transforms, Image reconstruction, Task analysis, Transforms, Adaptation models, Transformers, Video inpainting, gradient-weighted reconstruction loss BibRef

Fu, T.J.[Tsu-Jui], Yu, L.C.[Li-Cheng], Zhang, N.[Ning], Fu, C.Y.[Cheng-Yang], Su, J.C.[Jong-Chyi], Wang, W.Y.[William Yang], Bell, S.[Sean],
Tell Me What Happened: Unifying Text-guided Video Completion via Multimodal Masked Video Generation,
CVPR23(10681-10692)
IEEE DOI 2309
BibRef

Wu, Z.L.[Zhi-Liang], Sun, C.C.[Chang-Chang], Xuan, H.Y.[Han-Yu], Yan, Y.[Yan],
Deep Stereo Video Inpainting,
CVPR23(5693-5702)
IEEE DOI 2309
BibRef

Sun, H.Y.[Hong-Yi], Li, W.[Wanhua], Duan, Y.[Yueqi], Zhou, J.[Jie], Lu, J.W.[Ji-Wen],
Learning Adaptive Patch Generators for Mask-Robust Image Inpainting,
MultMed(25), 2023, pp. 4240-4252.
IEEE DOI 2310
BibRef

Yu, B.Y.[Bing-Yao], Li, W.[Wanhua], Li, X.[Xiu], Lu, J.W.[Ji-Wen], Zhou, J.[Jie],
Frequency-Aware Spatiotemporal Transformers for Video Inpainting Detection,
ICCV21(8168-8177)
IEEE DOI 2203
Frequency-domain analysis, Transformers, Spatiotemporal phenomena, Decoding, High frequency, Image and video manipulation detection and integrity methods. BibRef

Junayed, M.S.[Masum Shah], Islam, M.B.[Md Baharul],
Consistent Video Inpainting Using Axial Attention-Based Style Transformer,
MultMed(25), 2023, pp. 7494-7504.
IEEE DOI 2311
BibRef

Li, S.[Shibo], Zhu, S.Y.[Shu-Yuan], Huang, Y.Z.[Yu-Zhou], Liu, S.C.[Shuai-Cheng], Zeng, B.[Bing], Imran, M.A.[Muhammad Ali], Abbasi, Q.H.[Qammer H.], Cooper, J.[Jonathan],
Short-Long-Term Propagation-Based Video Inpainting,
MultMedMag(30), No. 4, October 2023, pp. 91-104.
IEEE DOI 2401
BibRef

Hou, J.C.[Jia-Cheng], Ji, Z.[Zhong], Yang, J.[Jinyu], Wang, C.J.[Cheng-Jie], Zheng, F.[Feng],
MCD-Net: Toward RGB-D Video Inpainting in Real-World Scenes,
IP(33), 2024, pp. 1095-1108.
IEEE DOI Code:
WWW Link. 2402
Image color analysis, Transformers, Correlation, Learning systems, Convolution, Video inpainting, RGB-D inpainting, RGB-D video dataset BibRef

Zhang, K.[Ke], Li, G.X.[Guan-Xiao], Su, Y.[Yu], Wang, J.Y.[Jing-Yu],
WTVI: A Wavelet-Based Transformer Network for Video Inpainting,
SPLetters(31), 2024, pp. 616-620.
IEEE DOI 2402
Discrete wavelet transforms, Transformers, Frequency-domain analysis, Wavelet domain, Semantics, vision transformer BibRef

Li, S.[Shibo], Zhu, S.Y.[Shu-Yuan], Ge, Y.[Yao], Zeng, B.[Bing], Imran, M.A.[Muhammad Ali], Abbasi, Q.H.[Qammer H.], Cooper, J.[Jonathan],
Depth-Guided Deep Video Inpainting,
MultMed(26), 2024, pp. 5860-5871.
IEEE DOI 2404
Transformers, Convolution, Image reconstruction, Optical flow, Image segmentation, content enhancement BibRef

Zhang, K.D.[Kai-Dong], Peng, J.L.[Jia-Lun], Fu, J.J.[Jing-Jing], Liu, D.[Dong],
Exploiting Optical Flow Guidance for Transformer-Based Video Inpainting,
PAMI(46), No. 7, July 2024, pp. 4977-4992.
IEEE DOI 2406
Transformers, Optical flow, Image motion analysis, Degradation, Spatiotemporal phenomena, Coherence, Flow completion, video inpainting BibRef

Quan, W.Z.[Wei-Ze], Chen, J.X.[Jia-Xi], Liu, Y.L.[Yan-Li], Yan, D.M.[Dong-Ming], Wonka, P.[Peter],
Deep Learning-Based Image and Video Inpainting: A Survey,
IJCV(132), No. 7, July 2024, pp. Pages2367-2400.
Springer DOI 2406
Survey, Inpainting. BibRef

Thiry, G.[Guillaume], Tang, H.[Hao], Timofte, R.[Radu], Van Gool, L.J.[Luc J.],
Towards Online Real-Time Memory-based Video Inpainting Transformers,
NTIRE24(6035-6044)
IEEE DOI 2410
Adaptation models, Computational modeling, Refining, Streaming media, Transformers, Transformers, Video Inpainting BibRef

Zhang, Z.X.[Zhi-Xing], Wu, B.[Bichen], Wang, X.Y.[Xiao-Yan], Luo, Y.Q.[Ya-Qiao], Zhang, L.X.[Lu-Xin], Zhao, Y.[Yinan], Vajda, P.[Peter], Metaxas, D.N.[Dimitris N.], Yu, L.C.[Li-Cheng],
AVID: Any-Length Video Inpainting with Diffusion Model,
CVPR24(7162-7172)
IEEE DOI 2410
Visualization, Computational modeling, Pipelines, Buildings, Diffusion models, Robustness, video inpainting, diffusion model BibRef

Zhang, X.J.[Xin-Jie], Yang, R.[Ren], He, D.[Dailan], Ge, X.T.[Xing-Tong], Xu, T.[Tongda], Wang, Y.[Yan], Qin, H.W.[Hong-Wei], Zhang, J.[Jun],
Boosting Neural Representations for Videos with a Conditional Decoder,
CVPR24(2556-2566)
IEEE DOI 2410
Interpolation, Computational modeling, Rate-distortion, Transforms, Minimization, Boosting, Entropy, Implicit neural representation, Video inpainting BibRef

Jin, J.J.[Jia-Jun],
Fast and high-quality video inpainting by efficiently patch searching and synthesizing,
CVIDL23(375-380)
IEEE DOI 2403
Deep learning, Visualization, Search problems, Propagation losses, Explosives, Quality assessment, patch searching and synthesizing BibRef

Zheng, W.Y.[Wei-Ying], Xu, C.[Cheng], Xu, X.[Xuemiao], Liu, W.X.[Wen-Xi], He, S.F.[Sheng-Feng],
CIRI: Curricular Inactivation for Residue-aware One-shot Video Inpainting,
ICCV23(12966-12976)
IEEE DOI Code:
WWW Link. 2401
BibRef

Zhou, S.[Shangchen], Li, C.Y.[Chong-Yi], Chan, K.C.K.[Kelvin C.K.], Change, C.[Chen],
ProPainter: Improving Propagation and Transformer for Video Inpainting,
ICCV23(10443-10452)
IEEE DOI 2401
BibRef

Lee, E.[Eunhye], Yoo, J.[Jinsu], Yang, Y.[Yunjeong], Baik, S.[Sungyong], Kim, T.H.[Tae Hyun],
Semantic-Aware Dynamic Parameter for Video Inpainting Transformer,
ICCV23(12903-12912)
IEEE DOI 2401
BibRef

Zhang, Y.[Yanni], Wu, Z.L.[Zhi-Liang], Yan, Y.[Yan],
PFTA-Net: Progressive Feature Alignment and Temporal Attention Fusion Networks for Video Inpainting,
ICIP23(191-195)
IEEE DOI 2312
BibRef

Chen, H.[Hao], Gwilliam, M.[Matthew], Lim, S.N.[Ser-Nam], Shrivastava, A.[Abhinav],
HNeRV: A Hybrid Neural Representation for Videos,
CVPR23(10270-10279)
IEEE DOI 2309
BibRef

Wu, Z.L.[Zhi-Liang], Xuan, H.Y.[Han-Yu], Sun, C.C.[Chang-Chang], Guan, W.[Weili], Zhang, K.[Kang], Yan, Y.[Yan],
Semi-Supervised Video Inpainting with Cycle Consistency Constraints,
CVPR23(22586-22595)
IEEE DOI 2309
BibRef

Kang, J.Y.[Jae-Yeon], Oh, S.W.[Seoung Wug], Kim, S.J.[Seon Joo],
Error Compensation Framework for Flow-Guided Video Inpainting,
ECCV22(XV:375-390).
Springer DOI 2211
BibRef

Zhang, K.D.[Kai-Dong], Fu, J.J.[Jing-Jing], Liu, D.[Dong],
Flow-Guided Transformer for Video Inpainting,
ECCV22(XVIII:74-90).
Springer DOI 2211
BibRef

Szeto, R.[Ryan], Corso, J.J.[Jason J.],
The DEVIL is in the Details: A Diagnostic Evaluation Benchmark for Video Inpainting,
CVPR22(21022-21031)
IEEE DOI 2210
Systematics, Codes, Benchmark testing, Cameras, Behavioral sciences, Datasets and evaluation, Video analysis and understanding BibRef

Li, Z.[Zhen], Lu, C.Z.[Cheng-Ze], Qin, J.H.[Jian-Hua], Guo, C.L.[Chun-Le], Cheng, M.M.[Ming-Ming],
Towards An End-to-End Framework for Flow-Guided Video Inpainting,
CVPR22(17541-17550)
IEEE DOI 2210
Codes, Pipelines, Benchmark testing, Trajectory, Computational complexity, Low-level vision, Video analysis and understanding BibRef

Ren, J.J.[Jing-Jing], Zheng, Q.Q.[Qing-Qing], Zhao, Y.Y.[Yuan-Yuan], Xu, X.M.[Xue-Miao], Li, C.[Chen],
DLFormer: Discrete Latent Transformer for Video Inpainting,
CVPR22(3501-3510)
IEEE DOI 2210
Training, Visualization, Codes, Spatial coherence, Jitter, Transformers, Image and video synthesis and generation, Vision applications and systems BibRef

Zhang, K.[Kaidong], Fu, J.J.[Jing-Jing], Liu, D.[Dong],
Inertia-Guided Flow Completion and Style Fusion for Video Inpainting,
CVPR22(5972-5981)
IEEE DOI 2210
Training, Adaptive systems, Correlation, Navigation, Pipelines, Transforms, Resists, Low-level vision BibRef

Liu, R.[Rui], Deng, H.M.[Han-Ming], Huang, Y.Y.[Yang-Yi], Shi, X.Y.[Xiao-Yu], Lu, L.W.[Le-Wei], Sun, W.X.[Wen-Xiu], Wang, X.G.[Xiao-Gang], Dai, J.F.[Ji-Feng], Li, H.S.[Hong-Sheng],
FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting,
ICCV21(14020-14029)
IEEE DOI 2203
Codes, Computational modeling, Transformers, Tokenization, Task analysis, Image and video synthesis, Low-level and physics-based vision BibRef

Lao, D.[Dong], Zhu, P.H.[Pei-Hao], Wonka, P.[Peter], Sundaramoorthi, G.[Ganesh],
Flow-Guided Video Inpainting with Scene Templates,
ICCV21(14579-14588)
IEEE DOI 2203
Interpolation, Annotations, Aggregates, Benchmark testing, Distortion, Filling, Image and video synthesis, Video analysis and understanding BibRef

Ouyang, H.[Hao], Wang, T.F.[Teng-Fei], Chen, Q.F.[Qi-Feng],
Internal Video Inpainting by Implicit Long-range Propagation,
ICCV21(14559-14568)
IEEE DOI 2203
Training, Learning systems, Semantics, Fitting, Streaming media, Real-time systems, Image and video synthesis, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Zou, X.[Xueyan], Yang, L.J.[Lin-Jie], Liu, D.[Ding], Lee, Y.J.[Yong Jae],
Progressive Temporal Feature Alignment Network for Video Inpainting,
CVPR21(16443-16452)
IEEE DOI 2111
Deep learning, Visualization, Image resolution, Convolution, Feature extraction BibRef

Lu, X.T.[Xu-Tong], Zhang, J.F.[Jian-Fu],
Danet: Deformable Alignment Network for Video Inpainting,
MMMod21(I:430-442).
Springer DOI 2106
BibRef

Andris, S.[Sarah], Peter, P.[Pascal], Mohideen, R.M.K.[Rahul Mohideen Kaja], Weickert, J.[Joachim], Hoffmann, S.[Sebastian],
Inpainting-based Video Compression in FullHD,
SSVM21(425-436).
Springer DOI 2106
BibRef

Liao, M.[Miao], Lu, F.X.[Fei-Xiang], Zhou, D.F.[Ding-Fu], Zhang, S.[Sibo], Li, W.[Wei], Yang, R.G.[Rui-Gang],
DVI: Depth Guided Video Inpainting for Autonomous Driving,
ECCV20(XXI:1-17).
Springer DOI 2011
BibRef

Li, A.[Ang], Zhao, S.S.[Shan-Shan], Ma, X.J.[Xing-Jun], Gong, M.M.[Ming-Ming], Qi, J.Z.[Jian-Zhong], Zhang, R.[Rui], Tao, D.C.[Da-Cheng], Kotagiri, R.[Ramamohanarao],
Short-term and Long-term Context Aggregation Network for Video Inpainting,
ECCV20(IV:728-743).
Springer DOI 2011
BibRef

Zeng, Y.H.[Yan-Hong], Fu, J.L.[Jian-Long], Chao, H.Y.[Hong-Yang],
Learning Joint Spatial-temporal Transformations for Video Inpainting,
ECCV20(XVI: 528-543).
Springer DOI 2010
BibRef

Hirohashi, Y., Narioka, K., Suganuma, M., Liu, X., Tamatsu, Y., Okatani, T.,
Removal of Image Obstacles for Vehicle-mounted Surrounding Monitoring Cameras by Real-time Video Inpainting,
VAS20(857-866)
IEEE DOI 2008
Image restoration, Optical imaging, Streaming media, Real-time systems, Estimation, Monitoring, Vehicles BibRef

Xu, Q., Zhang, H., Wang, W., Belhumeur, P.N., Neumann, U.,
Stochastic Dynamics for Video Infilling,
WACV20(2703-2712)
IEEE DOI 2006
Stochastic processes, Interpolation, Task analysis, Dynamics, Cameras, Bidirectional control, Coherence BibRef

Oh, S.W., Lee, S., Lee, J., Kim, S.J.,
Onion-Peel Networks for Deep Video Completion,
ICCV19(4402-4411)
IEEE DOI 2004
image restoration, image sequences, learning (artificial intelligence), neural nets, BibRef

Chang, Y., Liu, Z.Y., Lee, K., Hsu, W.,
Free-Form Video Inpainting With 3D Gated Convolution and Temporal PatchGAN,
ICCV19(9065-9074)
IEEE DOI 2004
convolutional neural nets, digital forensics, image motion analysis, learning (artificial intelligence), Painting BibRef

Hernandez, A., Gall, J., Moreno, F.,
Human Motion Prediction via Spatio-Temporal Inpainting,
ICCV19(7133-7142)
IEEE DOI 2004
image motion analysis, image sequences, learning (artificial intelligence), motion estimation, Training BibRef

Lee, S., Oh, S.W., Won, D., Kim, S.J.,
Copy-and-Paste Networks for Deep Video Inpainting,
ICCV19(4412-4420)
IEEE DOI 2004
image restoration, learning (artificial intelligence), neural nets, object detection, optimisation, Optical feedback BibRef

Zhang, H., Mai, L., Jin, H., Wang, Z., Xu, N., Collomosse, J.P.,
An Internal Learning Approach to Video Inpainting,
ICCV19(2720-2729)
IEEE DOI 2004
image restoration, image sequences, image texture, learning (artificial intelligence), video signal processing, Task analysis BibRef

Kim, D.[Dahun], Woo, S.[Sanghyun], Lee, J.Y.[Joon-Young], Kweon, I.S.[In So],
Deep Video Inpainting,
CVPR19(5785-5794).
IEEE DOI 2002
BibRef

Vogel, C.[Christoph], Knöbelreiter, P.[Patrick], Pock, T.[Thomas],
Learning Energy Based Inpainting for Optical Flow,
ACCV18(VI:340-356).
Springer DOI 1906
BibRef

Murase, R., Zhang, Y., Okatani, T.,
Video-Rate Video Inpainting,
WACV19(1553-1561)
IEEE DOI 1904
convolutional neural nets, image restoration, image sequences, video signal processing, video inpainting, video-rate, Real-time systems BibRef

Liu, W.Q.[Wen-Qian], Sharma, A.[Abhishek], Camps, O.I.[Octavia I.], Sznaier, M.[Mario],
DYAN: A Dynamical Atoms-Based Network for Video Prediction,
ECCV18(XII: 175-191).
Springer DOI 1810
BibRef

Oliver, M.[Maria], Raad, L.[Lara], Ballester, C.[Coloma], Haro, G.[Gloria],
Motion Inpainting by an Image-Based Geodesic AMLE Method,
ICIP18(2267-2271)
IEEE DOI 1809
Optical imaging, Adaptive optics, Optical sensors, Nonlinear optics, Geometrical optics, Integrated optics, anisotropic methods
See also On Anisotropic Optical Flow Inpainting Algorithms. BibRef

Bokov, A., Vatolin, D.,
100+ Times Faster Video Completion by Optical-Flow-Guided Variational Refinement,
ICIP18(2122-2126)
IEEE DOI 1809
Optical imaging, Optimization, Lighting, Spatiotemporal phenomena, Image reconstruction, Estimation, Pipelines, Video completion, inpainting BibRef

Siddique, A., Lee, S.,
Video Inpainting for Arbitrary Foreground Object Removal,
WACV18(1755-1763)
IEEE DOI 1806
image sequences, object detection, video signal processing, arbitrary foreground object removal, complex visual pattern, Visualization BibRef

Le, T.T., Almansa, A., Gousseau, Y., Masnou, S.,
Motion-consistent video inpainting,
ICIP17(2094-2098)
IEEE DOI 1803
Video inpainting, optical flow, patches, video editing, video restoration BibRef

Le, T.T., Almansa, A., Gousseau, Y., Masnou, S.,
Demonstration abstract: Motion-consistent video inpainting,
ICIP17(4587-4587)
IEEE DOI 1803
Cameras, Complexity theory, Image reconstruction, Optical sensors, Sensitivity, Task analysis, Visual systems BibRef

Mazaheri, A., Zhang, D., Shah, M.,
Video Fill In the Blank Using LR/RL LSTMs with Spatial-Temporal Attentions,
ICCV17(1416-1425)
IEEE DOI 1802
image representation, learning (artificial intelligence), recurrent neural nets, video coding, LR LSTMs, RL LSTMs, VFIB, Visualization BibRef

Morales, C., Roxas, M., Okamoto, Y., Ono, S., Oishi, T., Ikeuchi, K.,
Outdoor omnidirectional video completion via depth estimation by motion analysis,
ICPR16(3945-3950)
IEEE DOI 1705
Cameras, Image color analysis, Integrated circuits, Optical propagation, Spatiotemporal phenomena, Trajectory BibRef

Xiao, Y.D.[Yu-Dong], Suo, J.[Jinli], Bian, L.H.[Li-Heng], Zhang, L.[Lei], Dai, Q.H.[Qiong-Hai],
Automatic inpainting of linearly related video frames,
ICIP14(4692-4696)
IEEE DOI 1502
Brightness BibRef

Strobel, M.[Michael], Diebold, J.[Julia], Cremers, D.[Daniel],
Flow and Color Inpainting for Video Completion,
GCPR14(293-304).
Springer DOI 1411
BibRef

Sun, W.X.[Wen-Xiu], Au, O.C.[Oscar C.], Xu, L.F.[Ling-Feng], Li, Y.J.[Yu-Jun], Hu, W.[Wei],
Novel temporal domain hole filling based on background modeling for view synthesis,
ICIP12(2721-2724).
IEEE DOI 1302
BibRef

Granados, M.[Miguel], Kim, K.I.[Kwang In], Tompkin, J.[James], Kautz, J.[Jan], Theobalt, C.[Christian],
Background Inpainting for Videos with Dynamic Objects and a Free-Moving Camera,
ECCV12(I: 682-695).
Springer DOI 1210
BibRef

Biswas, M.[Mainak], Namboodiri, V.[Vipin],
On handling of occlusion for frame rate up-conversion using video in-painting,
ICIP10(785-788).
IEEE DOI 1009
BibRef

Kawai, N.[Norihiko], Machikita, K.[Kotaro], Sato, T.[Tomokazu], Yokoya, N.[Naokazu],
Generation of an Omnidirectional Video without Invisible Areas Using Image Inpainting,
ACCV09(II: 359-370).
Springer DOI 0909
BibRef

Hyun, D.Y.[Dae-Young], Heu, J.H.[Jun-Hee], Kim, C.S.[Chang-Su], Lee, S.U.[Sang-Uk],
Region-based backlight compensation algorithm for images and videos,
ICIP10(3545-3548).
IEEE DOI 1009
BibRef

Lee, S.Y.[Soon-Young], Heu, J.H.[Jun-Hee], Kim, C.S.[Chang-Su], Lee, S.U.[Sang-Uk],
An object inpainting algorithm for multi-view video sequences,
ICIP08(533-536).
IEEE DOI 0810
BibRef

Ding, T.[Tao], Sznaier, M.[Mario], Camps, O.I.[Octavia I.],
A Rank Minimization Approach to Video Inpainting,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Jain, V.[Vardhman], Narayanan, P.J.,
Video Completion for Indoor Scenes,
ICCVGIP06(409-420).
Springer DOI 0612
BibRef

Shen, Y.P.[Yu-Ping], Lu, F.[Fei], Cao, X.C.[Xiao-Chun], Foroosh, H.[Hassan],
Video Completion for Perspective Camera Under Constrained Motion,
ICPR06(III: 63-66).
IEEE DOI 0609
BibRef

DuFaux, F.[Frédéric], Ebrahimi, T.[Touradj],
Scrambling for Video Surveillance with Privacy,
PRIV06(160).
IEEE DOI 0609
Really the opposite of inpainting. Based on transform domain scrambling. BibRef

Shiratori, T.[Takaaki], Matsushita, Y.[Yasuyuki], Tang, X.[Xiaoou], Kang, S.B.[Sing Bing],
Video Completion by Motion Field Transfer,
CVPR06(I: 411-418).
IEEE DOI 0606
BibRef

Cocquerez, J.P.[Jean Pierre], Chanas, L.[Laurent], Blanc-Talon, J.[Jacques],
Simultaneous Inpainting and Motion Estimation of Highly Degraded Video-Sequences,
SCIA03(685-692).
Springer DOI 0310
BibRef

Kokaram, A., Collis, B., Robinson, S.,
A Bayesian framework for recursive object removal in movie post-production,
ICIP03(I: 937-940).
IEEE DOI 0312
BibRef

Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Tensor Completion .