liwangcs/awesome-video-segmentation

papers about video segmentation

awesome-video-segmentation

collecting the papers about "video segmentation"

some way to extend the result:

• video segmentation for Microsoft Academic Search

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2010

2011

• Ayvaci A, Soatto S. Detachable object detection: Segmentation and depth ordering from short-baseline video[J]. IEEE transactions on pattern analysis and machine intelligence, 2012, 34(10): 1942-1951.
• Lawto J, Gauvain J L, Lamel L, et al. A scalable video search engine based on audio content indexing and topic segmentation[J]. arXiv preprint arXiv:1111.6265, 2011.

2012

• Cheng H T, Ahuja N. Exploiting nonlocal spatiotemporal structure for video segmentation[C]//Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on. IEEE, 2012: 741-748.
• Xu C, Xiong C, Corso J J. Streaming hierarchical video segmentation[C]//European Conference on Computer Vision. Springer, Berlin, Heidelberg, 2012: 626-639.
• Lee J, Kwak S, Han B, et al. Online video segmentation by bayesian split-merge clustering[C]//European conference on computer vision. Springer Berlin Heidelberg, 2012: 856-869.
• Galasso F, Cipolla R, Schiele B. Video segmentation with superpixels[C]//Asian Conference on Computer Vision. Springer, Berlin, Heidelberg, 2012: 760-774.
• Di X, Chang H, Chen X. Multi-layer spectral clustering for video segmentation[C]//Asian Conference on Computer Vision. Springer, Berlin, Heidelberg, 2012: 1-12.
• Budvytis I, Badrinarayanan V, Cipolla R. MoT-Mixture of Trees Probabilistic Graphical Model for Video Segmentation[C]//BMVC. 2012, 1(2): 7.
• Xu C, Corso J J. Evaluation of super-voxel methods for early video processing[C]//Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on. IEEE, 2012: 1202-1209.

2013

• Jain A, Chatterjee S, Vidal R. Coarse-to-fine semantic video segmentation using supervoxel trees[C]//Proceedings of the IEEE International Conference on Computer Vision. 2013: 1865-1872.
• Galasso F, Shankar Nagaraja N, Jimenez Cardenas T, et al. A unified video segmentation benchmark: Annotation, metrics and analysis[C]//Proceedings of the IEEE International Conference on Computer Vision. 2013: 3527-3534.
• Palou G, Salembier P. Hierarchical video representation with trajectory binary partition tree[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2013: 2099-2106.
• Couprie C, Farabet C, LeCun Y, et al. Causal graph-based video segmentation[C]//Image Processing (ICIP), 2013 20th IEEE International Conference on. IEEE, 2013: 4249-4253.
• Şener O, Ugur K, Alatan A A. Efficient MRF energy propagation for video segmentation via bilateral filters[J]. IEEE Transactions on Multimedia, 2014, 16(5): 1292-1302.
• Friedman N, Russell S. Image segmentation in video sequences: A probabilistic approach[C]//Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence. Morgan Kaufmann Publishers Inc., 1997: 175-181.
• Dushnik D, Schclar A, Averbuch A. Video segmentation via diffusion bases[J]. arXiv preprint arXiv:1305.0218, 2013.
• Spina T V, Tepper M, Esler A, et al. Video human segmentation using fuzzy object models and its application to body pose estimation of toddlers for behavior studies[J]. arXiv preprint arXiv:1305.6918, 2013.
• Chakroun M, Wali A, Alimi A M. [MAS for video objects segmentation and tracking based on active contours and SURF descriptor(https://arxiv.org/abs/1308.0315)[J]. arXiv preprint arXiv:1308.0315, 2013.
• Xu C, Doell R F, Hanson S J, et al. A study of actor and action semantic retention in video supervoxel segmentation[J]. International Journal of Semantic Computing, 2013, 7(04): 353-375.

2014

• Galasso F, Keuper M, Brox T, et al. Spectral graph reduction for efficient image and streaming video segmentation[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2014: 49-56.
• Tripathi S, Hwang Y, Belongie S, et al. Improving streaming video segmentation with early and mid-level visual processing[C]//Applications of Computer Vision (WACV), 2014 IEEE Winter Conference on. IEEE, 2014: 477-484.
• Mahdi W, Ardebilian M, Chen L. Automatic video scene segmentation based on spatial-temporal clues and rhythm[J]. Networking and Information Systems Journal, 2000, 3(1): 27-52.
• Fragkiadaki K, Arbelaez P, Felsen P, et al. Learning to segment moving objects in videos[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015: 4083-4090.

2015

• Yin X, Chen J, Kramer D M. Joint Multi-Leaf Segmentation, Alignment, and Tracking from Fluorescence Plant Videos[J]. IEEE transactions on pattern analysis and machine intelligence, 2017.
• Yi S, Pavlovic V. Multi-cue structure preserving MRF for unconstrained video segmentation[C]//Proceedings of the IEEE International Conference on Computer Vision. 2015: 3262-3270.
• Tripathi S, Belongie S, Nguyen T. Beyond Semantic Image Segmentation: Exploring Efficient Inference in Video[J]. arXiv preprint arXiv:1507.01578, 2015.
• Kuehne H, Gall J, Serre T. Cooking in the kitchen: Recognizing and Segmenting Human Activities in Videos[J]. arXiv preprint arXiv:1508.06073, 2015.
• Kuehne H, Gall J, Serre T. An end-to-end generative framework for video segmentation and recognition[C]//Applications of Computer Vision (WACV), 2016 IEEE Winter Conference on. IEEE, 2016: 1-8.
• Tripathi S, Belongie S, Hwang Y, et al. Semantic video segmentation: Exploring inference efficiency[C]//SoC Design Conference (ISOCC), 2015 International. IEEE, 2015: 157-158.
• Narayana M, Hanson A, Learned-Miller E. Coherent motion segmentation in moving camera videos using optical flow orientations[C]//Proceedings of the IEEE International Conference on Computer Vision. 2013: 1577-1584.
• Taylor B, Karasev V, Soatto S. Causal video object segmentation from persistence of occlusions[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015: 4268-4276.[code]

2016

• Palazzo S, Spampinato C, Giordano D. Gamifying Video Object Segmentation[J]. arXiv preprint arXiv:1601.00825, 2016.
• Mirsharif Q, Sadani S, Shah S, et al. A Semi-Automated Method for Object Segmentation in Infant’s Egocentric Videos to Study Object Perception[C]//Proceedings of International Conference on Computer Vision and Image Processing. Springer, Singapore, 2017: 59-69.
• Wang J, Yeung S, Wang J, et al. Segmentation Rectification for Video Cutout via One-Class Structured Learning[J]. arXiv preprint arXiv:1602.04906, 2016.
• Yao J, Nielsen F. SSSC-AM: A unified framework for video co-segmentation by structured sparse subspace clustering with appearance and motion features[C]//Image Processing (ICIP), 2016 IEEE International Conference on. IEEE, 2016: 3957-3961.
• Bideau P, Learned-Miller E. It’s moving! A probabilistic model for causal motion segmentation in moving camera videos[C]//European Conference on Computer Vision. Springer International Publishing, 2016: 433-449.
• Khoreva A, Benenson R, Galasso F, et al. Improved image boundaries for better video segmentation[C]//Computer Vision–ECCV 2016 Workshops. Springer International Publishing, 2016: 773-788.
• Valipour S, Siam M, Jagersand M, et al. Recurrent Fully Convolutional Networks for Video Segmentation[C]//Applications of Computer Vision (WACV), 2017 IEEE Winter Conference on. IEEE, 2017: 29-36.
• Wang H, Raiko T, Lensu L, et al. Semi-supervised domain adaptation for weakly labeled semantic video object segmentation[C]//Asian Conference on Computer Vision. Springer, Cham, 2016: 163-179.
• Keuper M, Brox T. Point-wise mutual information-based video segmentation with high temporal consistency[C]//Computer Vision–ECCV 2016 Workshops. Springer International Publishing, 2016: 789-803.
• Spina T V, Falcao A X. Fomtrace: Interactive video segmentation by image graphs and fuzzy object models[J]. arXiv preprint arXiv:1606.03369, 2016.
• Jain S D, Grauman K. Click carving: Segmenting objects in video with point clicks[J]. arXiv preprint arXiv:1607.01115, 2016.
• Betancourt A, Morerio P, Barakova E, et al. Left/right hand segmentation in egocentric videos[J]. Computer Vision and Image Understanding, 2017, 154: 73-81.
• Mahasseni B, Todorovic S, Fern A. Approximate policy iteration for budgeted semantic video segmentation[J]. arXiv preprint arXiv:1607.07770, 2016.
• Drayer B, Brox T. Object detection, tracking, and motion segmentation for object-level video segmentation[J]. arXiv preprint arXiv:1608.03066, 2016.
• Shelhamer E, Rakelly K, Hoffman J, et al. Clockwork convnets for video semantic segmentation[C]//Computer Vision–ECCV 2016 Workshops. Springer International Publishing, 2016: 852-868.
• Fayyaz M, Saffar M H, Sabokrou M, et al. STFCN: Spatio-Temporal FCN for Semantic Video Segmentation[J]. arXiv preprint arXiv:1608.05971, 2016.
• Chandrajit M, Girisha R, Vasudev T, et al. Cast and Self Shadow Segmentation in Video Sequences using Interval based Eigen Value Representation[J]. CoRR, 2016.
• Cuffaro G, Becattini F, Baecchi C, et al. Segmentation Free Object Discovery in Video[C]//Computer Vision–ECCV 2016 Workshops. Springer International Publishing, 2016: 25-31.
• Chiu W C, Galasso F, Fritz M. Towards Segmenting Consumer Stereo Videos: Benchmark, Baselines and Ensembles[C]//Asian Conference on Computer Vision. Springer, Cham, 2016: 378-395.
• Prasath V B. Polyp detection and segmentation from video capsule endoscopy: A review[J]. Journal of Imaging, 2016, 3(1): 1.
• Jonna S, Nakka K K, Sahay R R. Deep learning based fence segmentation and removal from an image using a video sequence[C]//Computer Vision–ECCV 2016 Workshops. Springer International Publishing, 2016: 836-851.
• Mustikovela S K, Yang M Y, Rother C. Can Ground Truth Label Propagation from Video help Semantic Segmentation?[C]//Computer Vision–ECCV 2016 Workshops. Springer International Publishing, 2016: 804-820.
• 【OSVOS】Caelles S, Maninis K K, Pont-Tuset J, et al. One-shot video object segmentation[C]//CVPR 2017. IEEE, 2017.[code;code;code]
• Siam M, Valipour S, Jagersand M, et al. Convolutional Gated Recurrent Networks for Video Segmentation[J]. arXiv preprint arXiv:1611.05435, 2016.
• Khoreva A, Perazzi F, Benenson R, et al. Learning video object segmentation from static images[J]. arXiv preprint arXiv:1612.02646, 2016.
• Zhang K, Li X, Liu Q. Unsupervised Video Segmentation via Spatio-Temporally Nonlocal Appearance Learning[J]. arXiv preprint arXiv:1612.08169, 2016.
• Nilsson D, Sminchisescu C. Semantic video segmentation by gated recurrent flow propagation[J]. arXiv preprint arXiv:1612.08871, 2016.
• Tsai Y H, Yang M H, Black M J. Video segmentation via object flow[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2016: 3899-3908.[code]

2017

• Hong S, Yeo D, Kwak S, et al. Weakly Supervised Semantic Segmentation using Web-Crawled Videos[J]. arXiv preprint arXiv:1701.00352, 2017.
• Jain S D, Xiong B, Grauman K. Fusionseg: Learning to combine motion and appearance for fully automatic segmention of generic objects in videos[J]. arXiv preprint arXiv:1701.05384, 2017.
• Wang W, Bing S. Super-trajectory for video segmentation[J]. arXiv preprint arXiv:1702.08634, 2017.
• Le H, Nguyen V, Yu C P, et al. Geodesic Distance Histogram Feature for Video Segmentation[C]//Asian Conference on Computer Vision. Springer, Cham, 2016: 275-290.
• Pont-Tuset J, Perazzi F, Caelles S, et al. The 2017 davis challenge on video object segmentation[J]. arXiv preprint arXiv:1704.00675, 2017.
• Caelles S, Chen Y, Pont-Tuset J, et al. Semantically-Guided Video Object Segmentation[J]. arXiv preprint arXiv:1704.01926, 2017.
• Talavera E, Dimiccoli M, Bolanos M, et al. R-clustering for egocentric video segmentation[C]//Iberian Conference on Pattern Recognition and Image Analysis. Springer, Cham, 2015: 327-336.
• Griffin B A, Corso J J. Video Object Segmentation using Supervoxel-Based Gerrymandering[J]. arXiv preprint arXiv:1704.05165, 2017.
• Haller E, Leordeanu M. Unsupervised object segmentation in video by efficient selection of highly probable positive features[J]. arXiv preprint arXiv:1704.05674, 2017.
• Tokmakov P, Alahari K, Schmid C. Learning Video Object Segmentation with Visual Memory[J]. arXiv preprint arXiv:1704.05737, 2017.
• Wang L, Xiong Y, Wang Z, et al. Temporal Segment Networks for Action Recognition in Videos[J]. arXiv preprint arXiv:1705.02953, 2017.
• Ding L, Xu C. TricorNet: A Hybrid Temporal Convolutional and Recurrent Network for Video Action Segmentation[J]. arXiv preprint arXiv:1705.07818, 2017.
• Voigtlaender P, Leibe B. Online adaptation of convolutional neural networks for video object segmentation[J]. arXiv preprint arXiv:1706.09364, 2017.
• Vora A, Raman S. Flow-free video object segmentation[J]. arXiv preprint arXiv:1706.09544, 2017.
• Lee S, Kim D, Lee M, et al. Where to Play: Retrieval of Video Segments using Natural-Language Queries[J]. arXiv preprint arXiv:1707.00251, 2017.
• Sharir G, Smolyansky E, Friedman I. Video object segmentation using tracked object proposals[J]. arXiv preprint arXiv:1707.06545, 2017.
• Saha S, Singh G, Sapienza M, et al. Spatio-temporal human action localisation and instance segmentation in temporally untrimmed videos[J]. arXiv preprint arXiv:1707.07213, 2017.
• Guo C, Lai J, Xie X. Motion-Appearance Interactive Encoding for Object Segmentation in Unconstrained Videos[J]. arXiv preprint arXiv:1707.07857, 2017.
• Li X, Qi Y, Wang Z, et al. Video object segmentation with re-identification[J]. arXiv preprint arXiv:1708.00197, 2017.
• Ren W, Pan J, Cao X, et al. Video Deblurring via Semantic Segmentation and Pixel-Wise Non-Linear Kernel[J]. arXiv preprint arXiv:1708.03423, 2017.
• Saleh F S, Aliakbarian M S, Salzmann M, et al. Bringing background into the foreground: Making all classes equal in weakly-supervised video semantic segmentation[C]//2017 IEEE International Conference on Computer Vision (ICCV). IEEE, 2017: 2125-2135.
• Yoon J S, Rameau F, Kim J, et al. Pixel-Level Matching for Video Object Segmentation using Convolutional Neural Networks[C]//2017 IEEE International Conference on Computer Vision (ICCV). IEEE, 2017: 2186-2195.
• Shivakumara P, Guru D S, Basavaraju H T. Color and Gradient Features for Text Segmentation from Video Frames[M]//Multimedia Processing, Communication and Computing Applications. Springer, New Delhi, 2013: 267-278.
• Cheng J, Liu S, Tsai Y H, et al. Learning to segment instances in videos with spatial propagation network[J]. arXiv preprint arXiv:1709.04609, 2017.
• Maninis K K, Caelles S, Chen Y, et al. Video Object Segmentation Without Temporal Information[J]. arXiv preprint arXiv:1709.06031, 2017.
• Cheng J, Tsai Y H, Wang S, et al. SegFlow: Joint Learning for Video Object Segmentation and Optical Flow[C]//2017 IEEE International Conference on Computer Vision (ICCV). IEEE, 2017: 686-695.[code]
• Hipiny I, Ujir H, Minoi J L, et al. Unsupervised Segmentation of Action Segments in Egocentric Videos using Gaze[J]. arXiv preprint arXiv:1710.00187, 2017.
• Ke W, Zhu Y, Yu L. Automatic Streaming Segmentation of Stereo Video Using Bilateral Space[J]. arXiv preprint arXiv:1710.03488, 2017.
• Anjum N. Evaluation of Availability of Initial-segments of Video Files in Device-to-Device (D2D) Network[J]. arXiv preprint arXiv:1710.07083, 2017.
• Park S J, Hong K S. Video Semantic Object Segmentation by Self-Adaptation of DCNN[J]. arXiv preprint arXiv:1711.08180, 2017.
• Hou R, Chen C, Shah M. An End-to-end 3D Convolutional Neural Network for Action Detection and Segmentation in Videos[J]. arXiv preprint arXiv:1712.01111, 2017.

2018

• Benard A, Gygli M. Interactive Video Object Segmentation in the Wild[J]. arXiv preprint arXiv:1801.00269, 2017.
• Li S, Seybold B, Vorobyov A, et al. Instance Embedding Transfer to Unsupervised Video Object Segmentation[J]. arXiv preprint arXiv:1801.00908, 2018.
• Wang W, Shen J, Yang R, et al. Saliency-aware video object segmentation[J]. IEEE transactions on pattern analysis and machine intelligence, 2018, 40(1): 20-33.[code]