18.3.4.1 Video Object Segmentation

Qi, B.[Bin], Ghazal, M.[Mohammed], Amer, A.[Aishy],
Robust Global Motion Estimation Oriented to Video Object Segmentation,
IP(17), No. 6, June 2008, pp. 958-967.
IEEE DOI 0711
BibRef
Earlier: A1, A3, Only:
Robust and Fast Global Motion Estimation Oriented to Video Object Segmentation,
ICIP05(I: 153-156).
IEEE DOI 0512
BibRef

Yang, J., Price, B., Shen, X., Lin, Z., Yuan, J.,
Fast Appearance Modeling for Automatic Primary Video Object Segmentation,
IP(25), No. 2, February 2016, pp. 503-515.
IEEE DOI 1601
Adaptation models BibRef

Koh, Y.J., Kim, C.S.,
Unsupervised Primary Object Discovery in Videos Based on Evolutionary Primary Object Modeling With Reliable Object Proposals,
IP(26), No. 11, November 2017, pp. 5203-5216.
IEEE DOI 1709
BibRef
And:
Primary Object Segmentation in Videos Based on Region Augmentation and Reduction,
CVPR17(7417-7425)
IEEE DOI 1711
Color, Motion segmentation, Object segmentation, Proposals, Target tracking, Video sequences, Videos. POD algorithm, evolutionary primary object modeling technique, foreground confidence, motion-based object proposals, BibRef

Koh, Y.J., Kim, C.S.,
CDTS: Collaborative Detection, Tracking, and Segmentation for Online Multiple Object Segmentation in Videos,
ICCV17(3621-3629)
IEEE DOI 1802
image segmentation, image sequences, object detection, object tracking, video signal processing, CDTS, Videos BibRef

Jang, W.D.[Won-Dong], Kim, C.S.[Chang-Su],
Semi-supervised Video Object Segmentation Using Multiple Random Walkers,
BMVC16(xx-yy).
HTML Version. 1805
BibRef

Koh, Y.J.[Yeong Jun], Lee, Y.Y.[Young-Yoon], Kim, C.S.[Chang-Su],
Sequential Clique Optimization for Video Object Segmentation,
ECCV18(XIV: 537-556).
Springer DOI 1810
BibRef

Koh, Y.J., Jang, W.D.[Won-Dong], Kim, C.S.[Chang-Su],
POD: Discovering Primary Objects in Videos Based on Evolutionary Refinement of Object Recurrence, Background, and Primary Object Models,
CVPR16(1068-1076)
IEEE DOI 1612
BibRef

Jang, W.D.[Won-Dong], Kim, C.S.[Chang-Su],
Online Video Object Segmentation via Convolutional Trident Network,
CVPR17(7474-7483)
IEEE DOI 1711
Decoding, Feature extraction, Image segmentation, Motion segmentation, Object segmentation, Streaming media, Target, tracking BibRef

Lee, S.H., Jang, W.D.[Won-Dong], Kim, C.S.[Chang-Su],
Contour-Constrained Superpixels for Image and Video Processing,
CVPR17(5863-5871)
IEEE DOI 1711
Cost function, Image color analysis, Image segmentation, Labeling, Linear programming, Pattern, matching BibRef

Jang, W.D.[Won-Dong], Lee, C., Kim, C.S.[Chang-Su],
Primary Object Segmentation in Videos via Alternate Convex Optimization of Foreground and Background Distributions,
CVPR16(696-704)
IEEE DOI 1612
BibRef

Jang, W.D.[Won-Dong], Kim, C.S.[Chang-Su],
Streaming Video Segmentation via Short-Term Hierarchical Segmentation and Frame-by-Frame Markov Random Field Optimization,
ECCV16(VI: 599-615).
Springer DOI 1611
BibRef

Liu, Z., Wang, L., Hua, G., Zhang, Q., Niu, Z., Wu, Y., Zheng, N.,
Joint Video Object Discovery and Segmentation by Coupled Dynamic Markov Networks,
IP(27), No. 12, December 2018, pp. 5840-5853.
IEEE DOI 1810
Object segmentation, Noise measurement, Proposals, Markov random fields, Task analysis, Probabilistic logic, probabilistic graphical model BibRef

Bhatti, A.H.[Asma Hamza], Ur Rahman, A.[Anis], Butt, A.A.[Asad Anwar],
Unsupervised video object segmentation using conditional random fields,
SIViP(13), No. 1, February 2019, pp. 9-16.
WWW Link. 1901
BibRef
Earlier:
Video segmentation using spectral clustering on superpixels,
ICIP16(869-873)
IEEE DOI 1610
Color BibRef

Gu, S.[Song], Wang, J.[Jian], Du, Y.J.[Ying-Jie], Zhang, W.R.[Wei-Rui], Hao, W.[Wei], Zhou, D.M.[Dong-Mei],
Online video object segmentation via LRS representation,
IET-CV(13), No. 5, August 2019, pp. 469-479.
DOI Link 1908
BibRef

Chacon-Murguia, M.I.[Mario I.], Guzman-Pando, A.[Abimael], Ramirez-Alonso, G.[Graciela], Ramirez-Quintana, J.A.[Juan A.],
A novel instrument to compare dynamic object detection algorithms,
IVC(88), 2019, pp. 19-28.
Elsevier DOI 1908
Evaluation, Motion Segmentation. Analysis of Video object detection. Dynamic object detection, Algorithm methodology comparison, Video analysis BibRef

Guzman-Pando, A.[Abimael], Chacon-Murguia, M.I.[Mario I.],
DeepFoveaNet: Deep Fovea Eagle-Eye Bioinspired Model to Detect Moving Objects,
IP(30), 2021, pp. 7090-7100.
IEEE DOI 2108
Biological system modeling, Birds, Databases, Visualization, Training, Feature extraction, Brain modeling, eagle vision system BibRef

Zhuo, T., Cheng, Z., Zhang, P., Wong, Y., Kankanhalli, M.,
Unsupervised Online Video Object Segmentation With Motion Property Understanding,
IP(29), No. 1, 2020, pp. 237-249.
IEEE DOI 1910
image denoising, image fusion, image motion analysis, image segmentation, object detection, unsupervised learning, video understanding BibRef

Chen, Y.W.[Yi-Wen], Tsai, Y.H.[Yi-Hsuan], Lin, Y.Y.[Yen-Yu], Yang, M.H.[Ming-Hsuan],
VOSTR: Video Object Segmentation via Transferable Representations,
IJCV(128), No. 4, April 2020, pp. 931-949.
Springer DOI 2004
BibRef

Chen, Y.W.[Yi-Wen], Tsai, Y.H.[Yi-Hsuan], Yang, C.Y.[Chu-Ya], Lin, Y.Y.[Yen-Yu], Yang, M.H.[Ming-Hsuan],
Unseen Object Segmentation in Videos via Transferable Representations,
ACCV18(IV:615-631).
Springer DOI 1906
BibRef

Ammar, S.[Sirine], Bouwmans, T.[Thierry], Zaghden, N.[Nizar], Neji, M.[Mahmoud],
Deep detector classifier (DeepDC) for moving objects segmentation and classification in video surveillance,
IET-IPR(14), No. 8, 19 June 2020, pp. 1490-1501.
DOI Link 2005
BibRef

Tian, Y.[Yan], Cheng, G.[Guohua], Gelernter, J.[Judith], Yu, S.[Shihao], Song, C.[Chao], Yang, B.[Bailin],
Joint temporal context exploitation and active learning for video segmentation,
PR(100), 2020, pp. 107158.
Elsevier DOI 2005
Video segmentation, Deep learning BibRef

Sun, M.J.[Ming-Jie], Xiao, J.M.[Ji-Min], Lim, E.G.[Eng Gee], Xie, Y.C.[Yan-Chun], Feng, J.S.[Jia-Shi],
Adaptive ROI generation for video object segmentation using reinforcement learning,
PR(106), 2020, pp. 107465.
Elsevier DOI 2006
Model adaptation, Video object segmentation, Reinforcement learning, Training accelerate BibRef

Hu, P.[Ping], Wang, G.[Gang], Kong, X.F.[Xiang-Fei], Kuen, J.[Jason], Tan, Y.P.[Yap-Peng],
Motion-Guided Cascaded Refinement Network for Video Object Segmentation,
PAMI(42), No. 8, August 2020, pp. 1957-1967.
IEEE DOI 2007
BibRef
Earlier: CVPR18(1400-1409)
IEEE DOI 1812
Motion segmentation, Active contours, Optical imaging, Image segmentation, Optical propagation, Task analysis, spatial-temporal embedding. Image segmentation, Optical sensors, Level set, Object segmentation BibRef

Gui, Y., Tian, Y., Zeng, D.J., Xie, Z.F., Cai, Y.Y.,
Reliable and Dynamic Appearance Modeling and Label Consistency Enforcing for Fast and Coherent Video Object Segmentation With the Bilateral Grid,
CirSysVideo(30), No. 12, December 2020, pp. 4781-4795.
IEEE DOI 2012
Motion segmentation, Object segmentation, Reliability, Video sequences, Color, Computational modeling, Proposals, video object segmentation BibRef

Guzman-Pando, A.[Abimael], Chacon-Murguia, M.I.[Mario Ignacio], Chacon-Diaz, L.B.[Lucia B.],
Human-like evaluation method for object motion detection algorithms,
IET-CV(14), No. 8, December 2020, pp. 674-682.
DOI Link 2012
BibRef

Tan, Z.T.[Zhen-Tao], Liu, B.[Bin], Chu, Q.[Qi], Zhong, H.S.[Hang-Shi], Wu, Y.[Yue], Li, W.H.[Wei-Hai], Yu, N.H.[Neng-Hai],
Real Time Video Object Segmentation in Compressed Domain,
CirSysVideo(31), No. 1, January 2021, pp. 175-188.
IEEE DOI 2101
Feature extraction, Object segmentation, Motion segmentation, Real-time systems, Task analysis, Optical imaging, feature matching BibRef

Deng, J., Pan, Y., Yao, T., Zhou, W., Li, H., Mei, T.,
Single Shot Video Object Detector,
MultMed(23), 2021, pp. 846-858.
IEEE DOI 2103
Object detection, Detectors, Feature extraction, Proposals, Cats, Airplanes, Coherence, Video object detection, feature aggregation BibRef

Patil, P.W.[Prashant W.], Dudhane, A.[Akshay], Murala, S.[Subrahmanyam], Gonde, A.B.[Anil Balaji],
Deep Adversarial Network for Scene Independent Moving Object Segmentation,
SPLetters(28), 2021, pp. 489-493.
IEEE DOI 2103
Videos, Feature extraction, Training, Decoding, Generators, Analytical models, Transfer learning, video surveillance BibRef

Patil, P.W.[Prashant W.], Dudhane, A.[Akshay], Murala, S.[Subrahmanyam],
Multi-frame Recurrent Adversarial Network for Moving Object Segmentation,
WACV21(2301-2310)
IEEE DOI 2106
Training, Convolution, Motion segmentation, Object segmentation, Benchmark testing, Feature extraction BibRef

Patil, P.W.[Prashant W.], Biradar, K.M.[Kuldeep M.], Dudhane, A.[Akshay], Murala, S.[Subrahmanyam],
An End-to-End Edge Aggregation Network for Moving Object Segmentation,
CVPR20(8146-8155)
IEEE DOI 2008
Videos, Feature extraction, Decoding, Object segmentation, Optical imaging, Task analysis, Visualization BibRef

Chaudhary, S.[Sachin], Dudhane, A.[Akshay], Patil, P.W.[Prashant W.], Murala, S.[Subrahmanyam], Talbar, S.[Sanjay],
Motion estimation in hazy videos,
PRL(150), 2021, pp. 130-138.
Elsevier DOI 2109
Scene understanding, Motion estimation BibRef

Wang, X.G.[Xing-Gang], Huang, Z.J.[Zhao-Jin], Liao, B.C.[Ben-Cheng], Huang, L.C.[Li-Chao], Gong, Y.C.[Yong-Chao], Huang, C.[Chang],
Real-time and accurate object detection in compressed video by long short-term feature aggregation,
CVIU(206), 2021, pp. 103188.
Elsevier DOI 2104
BibRef

Jiang, C.[Cansen], Paudel, D.P.[Danda Pani], Fofi, D.[David], Fougerolle, Y.[Yohan], Demonceaux, C.[Cédric],
Moving Object Detection by 3D Flow Field Analysis,
ITS(22), No. 4, April 2021, pp. 1950-1963.
IEEE DOI 2104
Trajectory, Clustering algorithms, Motion segmentation, Image reconstruction, Dynamics, Tracking, 3D map reconstruction BibRef

Liu, W., Lin, G., Zhang, T., Liu, Z.,
Guided Co-Segmentation Network for Fast Video Object Segmentation,
CirSysVideo(31), No. 4, April 2021, pp. 1607-1617.
IEEE DOI 2104
Feature extraction, Object segmentation, Task analysis, Motion segmentation, Pipelines, Decoding, Search problems, semi-supervised BibRef

Wang, M.G.[Min-Gui], Cui, D.[Di], Wu, L.F.[Li-Fang], Jian, M.[Meng], Chen, Y.K.[Yu-Kun], Wang, D.[Dong], Liu, X.[Xu],
Weakly-supervised video object localization with attentive spatio-temporal correlation,
PRL(145), 2021, pp. 232-239.
Elsevier DOI 2104
Video object localization, Spatio-temporal correlation, Weakly-supervised BibRef

Chen, C.Z.[Chengli-Zhao], Wang, G.T.[Guo-Tao], Peng, C.[Chong], Fang, Y.M.[Yu-Ming], Zhang, D.W.[Ding-Wen], Qin, H.[Hong],
Exploring Rich and Efficient Spatial Temporal Interactions for Real-Time Video Salient Object Detection,
IP(30), 2021, pp. 3995-4007.
IEEE DOI 2104
Spatiotemporal phenomena, Convolution, Optical sensors, Decoding, Optical network units, Optical imaging, multiscale spatiotemporal deep features BibRef

Xu, M.Z.[Ming-Zhu], Fu, P.[Ping], Liu, B.[Bing], Li, J.B.[Jun-Bao],
Multi-Stream Attention-Aware Graph Convolution Network for Video Salient Object Detection,
IP(30), 2021, pp. 4183-4197.
IEEE DOI 2104
Spatiotemporal phenomena, Convolution, Data models, Visualization, Adaptation models, Object segmentation, Task analysis, node-wise attention mechanism BibRef

Huang, Y.[Ying], Jiang, Q.H.[Qing-Han], Qian, Y.[Ying],
A Novel Method for Video Moving Object Detection Using Improved Independent Component Analysis,
CirSysVideo(31), No. 6, June 2021, pp. 2217-2230.
IEEE DOI 2106
Object detection, Adaptive optics, Optical imaging, Integrated optics, Optical noise, Source separation, threshold BibRef

Zhao, Z.J.[Zong-Ji], Zhao, S.Y.[San-Yuan], Shen, J.B.[Jian-Bing],
Real-time and light-weighted unsupervised video object segmentation network,
PR(120), 2021, pp. 108120.
Elsevier DOI 2109
Unsupervised video object segmentation, Salient object detection BibRef

Yu, S.Y.[Si-Yue], Xiao, J.[Jimin], Zhang, B.F.[Bing-Feng], Lim, E.G.[Eng Gee], Zhao, Y.[Yao],
Fast pixel-matching for video object segmentation,
SP:IC(98), 2021, pp. 116373.
Elsevier DOI 2109
Non-local pixel matching, Mask-propagation, Encoder-decoder BibRef

Li, R.C.[Rong-Chang], Wu, X.J.[Xiao-Jun], Wu, C.[Cong], Xu, T.Y.[Tian-Yang], Kittler, J.V.[Josef V.],
Dynamic information enhancement for video classification,
IVC(114), 2021, pp. 104244.
Elsevier DOI 2109
Video classification, Spatiotemporal modelling, Explicitly encoding, Adaptive excitation BibRef

Patil, P.W.[Prashant W.], Dudhane, A.[Akshay], Kulkarni, A.[Ashutosh], Murala, S.[Subrahmanyam], Gonde, A.B.[Anil Balaji], Gupta, S.I.[Sun-Il],
An Unified Recurrent Video Object Segmentation Framework for Various Surveillance Environments,
IP(30), 2021, pp. 7889-7902.
IEEE DOI 2109
Decoding, Feature extraction, Object segmentation, Training, Task analysis, Optical imaging, Dynamics, various surveillance environments BibRef

Cheng, J.C.[Jing-Chun], Yuan, Y.[Yuhui], Li, Y.[Yali], Wang, J.D.[Jing-Dong], Wang, S.J.[Sheng-Jin],
Learning to Segment Video Object With Accurate Boundaries,
MultMed(23), 2021, pp. 3112-3123.
IEEE DOI 2109
Task analysis, Training, Object segmentation, Prediction algorithms, Image segmentation, Semantics, Proposals, joint learning BibRef

Han, L.[Liang], Wang, P.C.[Pi-Chao], Yin, Z.Z.[Zhao-Zheng], Wang, F.[Fan], Li, H.[Hao],
Context and Structure Mining Network for Video Object Detection,
IJCV(129), No. 10, October 2021, pp. 2927-2946.
Springer DOI 2110
BibRef

Wang, H.[Hui], Liu, W.B.[Wei-Bin], Xing, W.W.[Wei-Wei],
Video object segmentation via random walks on two-frame graphs comprising superpixels,
JVCIR(80), 2021, pp. 103293.
Elsevier DOI 2110
Random walks, Video object segmentation, Optical flow gradient, Spatiotemporal consistency BibRef

Xu, K.[Kai], Wen, L.Y.[Long-Yin], Li, G.R.[Guo-Rong], Huang, Q.M.[Qing-Ming],
Self-Supervised Deep TripleNet for Video Object Segmentation,
MultMed(23), 2021, pp. 3530-3539.
IEEE DOI 2110
Training, Object segmentation, Motion segmentation, Image matching, Video sequences, Task analysis, Annotations, self-supervised learning BibRef

Banerjee, S.[Sreya], VidalMata, R.G.[Rosaura G.], Wang, Z.Y.[Zhang-Yang], Scheirer, W.J.[Walter J.],
Report on UG2+ challenge Track 1: Assessing algorithms to improve video object detection and classification from unconstrained mobility platforms,
CVIU(213), 2021, pp. 103297.
Elsevier DOI 2112
Computational photography, Object recognition, Object detection, Evaluation protocols, Deep learning BibRef

Jin, R.[Ruibing], Lin, G.[Guosheng], Wen, C.[Changyun], Wang, J.[Jianliang], Liu, F.[Fayao],
Feature flow: In-network feature flow estimation for video object detection,
PR(122), 2022, pp. 108323.
Elsevier DOI 2112
Video object detection, Feature flow, Object detection, Video analysis, Deep convolutional neural network (DCNN) BibRef

Zhu, L.[Li], Xie, Z.[Zihao], Luo, J.[Jing], Qi, Y.H.[Yu-Hang], Liu, L.M.[Li-Man], Tao, W.B.[Wen-Bing],
Dynamic Object Detection Algorithm Based on Lightweight Shared Feature Pyramid,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Oh, S.W.[Seoung Wug], Lee, J.Y.[Joon-Young], Xu, N.[Ning], Kim, S.J.[Seon Joo],
Space-Time Memory Networks for Video Object Segmentation With User Guidance,
PAMI(44), No. 1, January 2022, pp. 442-455.
IEEE DOI 2112
BibRef
Earlier:
Video Object Segmentation Using Space-Time Memory Networks,
ICCV19(9225-9234)
IEEE DOI 2004
Object segmentation, Task analysis, Learning systems, Feature extraction, Runtime, Detectors, Visualization, memory networks. image segmentation, learning (artificial intelligence), query processing, video signal processing, Benchmark testing BibRef

Bethi, Y.R.T.[Yeshwanth Ravi Theja], Narayanan, S.[Sathyaprakash], Rangan, V.[Venkat], Chakraborty, A.[Anirban], Thakur, C.S.[Chetan Singh],
Real-Time Object Detection and Localization in Compressive Sensed Video,
ICIP21(1489-1493)
IEEE DOI 2201
Location awareness, Image coding, Memory management, Object detection, Streaming media, Cameras, Real-time systems, Compressive Sensing BibRef

Shih, C.H.[Chin-Hsuan], Tsai, W.J.[Wen-Jiin],
Hierarchical Embedding Guided Network for Video Object Segmentation,
ICIP21(1124-1128)
IEEE DOI 2201
Learning systems, Image segmentation, Annotations, Motion segmentation, Object segmentation, Feature extraction, hierarchical embedding BibRef

Ping-Yang, C.[Chen], Hsieh, J.W.[Jun-Wei], Gochoo, M.[Munkhjargal], Chen, Y.S.[Yong-Sheng],
Light-Weight Mixed Stage Partial Network for Surveillance Object Detection with Background Data Augmentation,
ICIP21(3333-3337)
IEEE DOI 2201
Roads, Surveillance, Image processing, Object detection, Benchmark testing, Computational efficiency, MSPNet, background subtraction BibRef

Bae, H.[Heechul], Song, S.[Soonyong], Park, J.[Junhee],
Occluded Video Instance Segmentation with Set Prediction Approach,
OVIS21(3843-3846)
IEEE DOI 2112
Motion segmentation, Streaming media, Benchmark testing, Real-time systems, Task analysis BibRef

Athar, A.[Ali], Mahadevan, S.[Sabarinath], Ošep, A.[Aljoša], Leal-Taixé, L.[Laura], Leibe, B.[Bastian],
A Single-Stage, Bottom-up Approach for Occluded VIS using Spatio-temporal Embeddings,
OVIS21(3851-3855)
IEEE DOI 2112
Video sequences, Benchmark testing, Task analysis BibRef

Huang, Z.Y.[Zi-Yuan], Zhang, S.[Shiwei], Jiang, J.W.[Jian-Wen], Tang, M.Q.[Ming-Qian], Jin, R.[Rong], Ang, M.H.[Marcelo H.],
Self-supervised Motion Learning from Static Images,
CVPR21(1276-1285)
IEEE DOI 2111
Training, Codes, Annotations, Pattern recognition, Task analysis, Videos BibRef

Hu, L.[Li], Zhang, P.[Peng], Zhang, B.[Bang], Pan, P.[Pan], Xu, Y.H.[Ying-Hui], Jin, R.[Rong],
Learning Position and Target Consistency for Memory-based Video Object Segmentation,
CVPR21(4142-4152)
IEEE DOI 2111
Object segmentation, Benchmark testing, Pattern recognition, Reliability, Task analysis BibRef

Ost, J.[Julian], Mannan, F.[Fahim], Thuerey, N.[Nils], Knodt, J.[Julian], Heide, F.[Felix],
Neural Scene Graphs for Dynamic Scenes,
CVPR21(2855-2864)
IEEE DOI 2111
Training, Extrapolation, Image color analysis, Neural networks, Training data, Object detection BibRef

Zhou, T.F.[Tian-Fei], Li, J.W.[Jian-Wu], Li, X.Y.[Xue-Yi], Shao, L.[Ling],
Target-Aware Object Discovery and Association for Unsupervised Video Multi-Object Segmentation,
CVPR21(6981-6990)
IEEE DOI 2111
Adaptation models, Target tracking, Estimation, Object segmentation, Feature extraction, Pattern recognition BibRef

Xie, H.[Haozhe], Yao, H.X.[Hong-Xun], Zhou, S.[Shangchen], Zhang, S.P.[Sheng-Ping], Sun, W.X.[Wen-Xiu],
Efficient Regional Memory Network for Video Object Segmentation,
CVPR21(1286-1295)
IEEE DOI 2111
Target tracking, Memory management, Object segmentation, Pattern recognition, Optical flow BibRef

Wang, H.C.[Hao-Chen], Jiang, X.L.[Xiao-Long], Ren, H.B.[Hai-Bing], Hu, Y.[Yao], Bai, S.[Song],
SwiftNet: Real-time Video Object Segmentation,
CVPR21(1296-1305)
IEEE DOI 2111
Codes, Redundancy, Memory management, Object segmentation, Streaming media, Real-time systems BibRef

Duke, B.[Brendan], Ahmed, A.[Abdalla], Wolf, C.[Christian], Aarabi, P.[Parham], Taylor, G.W.[Graham W.],
SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentation,
CVPR21(5908-5917)
IEEE DOI 2111
Codes, Runtime, Scalability, Computational modeling, Object segmentation, Transformers BibRef

Chen, H.X.[Hao-Xin], Wu, H.J.[Han-Jie], Zhao, N.[Nanxuan], Ren, S.[Sucheng], He, S.F.[Sheng-Feng],
Delving Deep into Many-to-many Attention for Few-shot Video Object Segmentation,
CVPR21(14035-14044)
IEEE DOI 2111
Image segmentation, Codes, Computational modeling, Object segmentation, Pattern recognition, Computational efficiency BibRef

Ren, S.[Sucheng], Liu, W.X.[Wen-Xi], Liu, Y.[Yongtuo], Chen, H.X.[Hao-Xin], Han, G.Q.[Guo-Qiang], He, S.F.[Sheng-Feng],
Reciprocal Transformations for Unsupervised Video Object Segmentation,
CVPR21(15430-15439)
IEEE DOI 2111
Optical filters, Transforms, Object segmentation, Coherence, Search problems, Pattern recognition BibRef

Park, H.[Hyojin], Yoo, J.[Jayeon], Jeong, S.[Seohyeong], Venkatesh, G.[Ganesh], Kwak, N.[Nojun],
Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Video Object Segmentation,
CVPR21(8401-8410)
IEEE DOI 2111
Degradation, Codes, Computational modeling, Object segmentation, Computer architecture, Logic gates BibRef

Ge, W.B.[Wen-Bin], Lu, X.[Xiankai], Shen, J.B.[Jian-Bing],
Video Object Segmentation Using Global and Instance Embedding Learning,
CVPR21(16831-16840)
IEEE DOI 2111
Annotations, Object segmentation, Pattern recognition, Task analysis BibRef

Lezki, H.[Hazal], Ozturk, I.A.[I. Ahu], Akpinar, M.A.[M. Akif], Yucel, M.K.[M. Kerim], Logoglu, K.B.[K. Berker], Erdem, A.[Aykut], Erdem, E.[Erkut],
Joint Exploitation of Features and Optical Flow for Real-Time Moving Object Detection on Drones,
CVUAV18(II:100-116).
Springer DOI 1905
BibRef

Garg, S.[Shubhika], Goel, V.[Vidit],
Mask Selection and Propagation for Unsupervised Video Object Segmentation,
WACV21(1679-1689)
IEEE DOI 2106
Pipelines, Neural networks, Object segmentation, Task analysis BibRef

Fujitake, M.[Masato], Sugimoto, A.[Akihiro],
Temporal Feature Enhancement Network with External Memory for Object Detection in Surveillance Video,
ICPR21(7684-7691)
IEEE DOI 2105
Visualization, Interpolation, Surveillance, Object detection, Streaming media, Traffic control, Feature extraction BibRef

Xu, M.Z.[Mu-Zhou], Zhong, S.[Shan], Liu, C.[Chunping], Gong, S.R.[Sheng-Rong], Wang, Z.H.[Zhao-Hui], Xia, Y.[Yu],
ACCLVOS: Atrous Convolution with Spatial-Temporal ConvLSTM for Video Object Segmentation,
ICPR21(2089-2096)
IEEE DOI 2105
Convolution, Target recognition, Video sequences, Spatial coherence, Coherence, Object segmentation, Streaming media, Convolution BibRef

Kim, J.[Jaekyum], Koh, J.[Junho], Lee, B.[Byeongwon], Yang, S.J.[Seung-Ji], Choi, J.W.[Jun Won],
Video Object Detection Using Object's Motion Context and Spatio-Temporal Feature Aggregation,
ICPR21(1604-1610)
IEEE DOI 2105
Correlation, Object detection, Detectors, Streaming media, Logic gates, Performance gain BibRef

Zheng, X.Y.[Xiao-Yang], Tan, X.[Xin], Guo, J.M.[Jian-Ming], Ma, L.Z.[Li-Zhuang],
Learning Object Deformation and Motion Adaption for Semi-supervised Video Object Segmentation,
ICPR21(8655-8662)
IEEE DOI 2105
Training, Adaptation models, Shape, Annotations, Video sequences, Training data, Object segmentation, video object segmentation, semi-supervision BibRef

Rahmon, G.[Gani], Bunyak, F.[Filiz], Seetharaman, G.[Guna], Palaniappan, K.[Kannappan],
Motion U-Net: Multi-cue Encoder-Decoder Network for Motion Segmentation,
ICPR21(8125-8132)
IEEE DOI 2105
Training, Tensors, Motion estimation, Video sequences, Transfer learning, Training data, moving object, U-Net BibRef

Siarohin, A.[Aliaksandr], Roy, S.[Subhankar], Lathuilière, S.[Stéphane], Tulyakov, S.[Sergey], Ricci, E.[Elisa], Sebe, N.[Nicu],
Motion-supervised Co-Part Segmentation,
ICPR21(9650-9657)
IEEE DOI 2105
Training, Deep learning, Image segmentation, Motion segmentation, Video sequences, Supervised learning, Streaming media BibRef

Arrigoni, F.[Federica], Magri, L.[Luca], Pajdla, T.[Tomas],
Motion Segmentation with Pairwise Matches and Unknown Number of Motions,
ICPR21(2896-2903)
IEEE DOI 2105
Motion segmentation, Fitting, Benchmark testing, Trajectory, Pattern recognition, Synchronization BibRef

Kardoost, A.[Amirhossein], Müller, S.[Sabine], Weickert, J.[Joachim], Keuper, M.[Margret],
Object Segmentation Tracking from Generic Video Cues,
ICPR21(623-630)
IEEE DOI 2105
Training, Navigation, Annotations, Video sequences, Estimation, Object segmentation, Task analysis BibRef

Azimi, F.[Fatemeh], Bischke, B.[Benjamin], Palacio, S.[Sebastian], Raue, F.[Federico], Hees, J.[Jörn], Dengel, A.[Andreas],
Revisiting Sequence-to-Sequence Video Object Segmentation with Multi-Task Loss and Skip-Memory,
ICPR21(5376-5383)
IEEE DOI 2105
Measurement, Visualization, Object segmentation, Memory modules, Pattern recognition, Task analysis BibRef

Seong, H.J.[Hong-Je], Hyun, J.[Junhyuk], Kim, E.T.[Eun-Tai],
Kernelized Memory Network for Video Object Segmentation,
ECCV20(XXII:629-645).
Springer DOI 2011
BibRef

Zhen, M.M.[Ming-Min], Li, S.W.[Shi-Wei], Zhou, L.[Lei], Shang, J.X.[Jia-Xiang], Feng, H.A.[Hao-An], Fang, T.[Tian], Quan, L.[Long],
Learning Discriminative Feature with CRF for Unsupervised Video Object Segmentation,
ECCV20(XXVII:445-462).
Springer DOI 2011
BibRef

Seo, S.[Seonguk], Lee, J.Y.[Joon-Young], Han, B.H.[Bo-Hyung],
Urvos: Unified Referring Video Object Segmentation Network with a Large-scale Benchmark,
ECCV20(XV:208-223).
Springer DOI 2011
BibRef

Li, Y., Chen, F., Yang, F., Li, Y., Jia, H., Xie, X.,
Fusion Target Attention Mask Generation Network For Video Segmentation,
ICIP20(2276-2280)
IEEE DOI 2011
Solid modeling, Object segmentation, Adaptation models, Training, Motion segmentation, Visualization, Convolution, loss function BibRef

Cho, S., Cho, M., Chung, T.y., Lee, H., Lee, S.,
CRVOS: Clue Refining Network For Video Object Segmentation,
ICIP20(2301-2305)
IEEE DOI 2011
Decoding, Object segmentation, Real-time systems, Streaming media, Deconvolution, Feature extraction, Convolution, Encoder-decoder architecture BibRef

Zhang, L.[Lu], Zhang, J.M.[Jian-Ming], Lin, Z.[Zhe], Mech, R.[Radomír], Lu, H.C.[Hu-Chuan], He, Y.[You],
Unsupervised Video Object Segmentation with Joint Hotspot Tracking,
ECCV20(XIV:490-506).
Springer DOI 2011
BibRef

Li, Y.[Yu], Shen, Z.[Zhuoran], Shan, Y.[Ying],
Fast Video Object Segmentation Using the Global Context Module,
ECCV20(X:735-750).
Springer DOI 2011
BibRef

Zhang, Y., Wu, Z., Peng, H., Lin, S.,
A Transductive Approach for Video Object Segmentation,
CVPR20(6947-6956)
IEEE DOI 2008
Object segmentation, Task analysis, Video sequences, Computational modeling, History, Estimation, Data models BibRef

Chen, X., Li, Z., Yuan, Y., Yu, G., Shen, J., Qi, D.,
State-Aware Tracker for Real-Time Video Object Segmentation,
CVPR20(9381-9390)
IEEE DOI 2008
Target tracking, Robustness, Task analysis, Pipelines, Object segmentation, State estimation, Video sequences BibRef

Luiten, J., Zulfikar, I.E., Leibe, B.,
UnOVOST: Unsupervised Offline Video Object Segmentation and Tracking,
WACV20(1989-1998)
IEEE DOI 2006
Task analysis, Proposals, Object segmentation, Forestry, Motion segmentation, Visualization, Tracking BibRef

Yang, Z.[Zhao], Wang, Q.[Qiang], Bertinetto, L.[Luca], Bai, S.[Song], Hu, W.M.[Wei-Ming], Torr, P.H.S.[Philip H.S.],
Anchor Diffusion for Unsupervised Video Object Segmentation,
ICCV19(931-940)
IEEE DOI 2004
image segmentation, image sequences, learning (artificial intelligence), object detection, Task analysis BibRef

Duarte, K., Rawat, Y., Shah, M.,
CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule Routing,
ICCV19(8479-8488)
IEEE DOI 2004
Code, Video Segmentation.
WWW Link. image motion analysis, image segmentation, image sequences, object tracking, video signal processing, CapsuleVOS, Computer architecture BibRef

Yang, Z., Li, P., Feng, Q., Wei, Y., Yang, Y.,
Going Deeper Into Embedding Learning for Video Object Segmentation,
YouTube-VOS19(697-700)
IEEE DOI 2004
image motion analysis, image segmentation, learning (artificial intelligence), object detection, object recognition BibRef

Luiten, J., Voigtlaender, P., Leibe, B.,
Exploring the Combination of PReMVOS, BoLTVOS and UnOVOST for the 2019 YouTube-VOS Challenge,
YouTube-VOS19(705-708)
IEEE DOI 2004
image segmentation, object detection, object tracking, video signal processing, UnOVOST, segmentation BibRef

Griffin, B.A.[Brent A.], Corso, J.J.[Jason J.],
Learning Object Depth from Camera Motion and Video Object Segmentation,
ECCV20(VII:295-312).
Springer DOI 2011
BibRef
Earlier:
BubbleNets: Learning to Select the Guidance Frame in Video Object Segmentation by Deep Sorting Frames,
CVPR19(8906-8915).
IEEE DOI 2002
BibRef

Bhat, G.[Goutam], Järemo Lawin, F.[Felix], Danelljan, M.[Martin], Robinson, A.[Andreas], Felsberg, M.[Michael], Van Gool, L.J.[Luc J.], Timofte, R.[Radu],
Learning What to Learn for Video Object Segmentation,
ECCV20(II:777-794).
Springer DOI 2011
BibRef

Robinson, A., Järemo Lawin, F.[Felix], Danelljan, M.[Martin], Khan, F.S.[Fahad Shahbaz], Felsberg, M.[Michael],
Learning Fast and Robust Target Models for Video Object Segmentation,
CVPR20(7404-7413)
IEEE DOI 2008
Image segmentation, Robustness, Object segmentation, Adaptation models, Data models, Training, Target tracking BibRef

Chen, Y., Pont-Tuset, J., Montes, A., Van Gool, L.J.,
Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning,
CVPR18(1189-1198)
IEEE DOI 1812
Object segmentation, Measurement, Task analysis, Adaptive optics, Feature extraction, Streaming media BibRef

Johnander, J.[Joakim], Danelljan, M.[Martin], Brissman, E.[Emil], Khan, F.S.[Fahad Shahbaz], Felsberg, M.[Michael],
A Generative Appearance Model for End-To-End Video Object Segmentation,
CVPR19(8945-8954).
IEEE DOI 2002
BibRef

Ventura, C.[Carles], Bellver, M.[Miriam], Girbau, A.[Andreu], Salvador, A.[Amaia], Marques, F.[Ferran], Giro-i-Nieto, X.[Xavier],
RVOS: End-To-End Recurrent Network for Video Object Segmentation,
CVPR19(5272-5281).
IEEE DOI 2002
BibRef

Xu, S.J.[Shuang-Jie], Liu, D.Z.[Dai-Zong], Bao, L.C.[Lin-Chao], Liu, W.[Wei], Zhou, P.[Pan],
MHP-VOS: Multiple Hypotheses Propagation for Video Object Segmentation,
CVPR19(314-323).
IEEE DOI 2002
BibRef

Khoreva, A.[Anna], Rohrbach, A.[Anna], Schiele, B.[Bernt],
Video Object Segmentation with Language Referring Expressions,
ACCV18(IV:123-141).
Springer DOI 1906
BibRef
And:
Video Object Segmentation with Referring Expressions,
VSeg18(IV:7-12).
Springer DOI 1905
BibRef

Han, J., Yang, L., Zhang, D., Chang, X., Liang, X.,
Reinforcement Cutting-Agent Learning for Video Object Segmentation,
CVPR18(9080-9089)
IEEE DOI 1812
Object segmentation, Task analysis, Search problems, Decision making, Tracking BibRef

Xiao, H., Feng, J., Lin, G., Liu, Y., Zhang, M.,
MoNet: Deep Motion Exploitation for Video Object Segmentation,
CVPR18(1140-1148)
IEEE DOI 1812
Motion segmentation, Feature extraction, Transforms, Optical imaging, Optical network units, Object segmentation, Optical propagation BibRef

Sokeh, H.S., Argyriou, V., Monekosso, D., Remagnino, P.,
Superframes, A Temporal Video Segmentation,
ICPR18(566-571)
IEEE DOI 1812
Clustering algorithms, Motion segmentation, Histograms, Databases, Image segmentation, Optical imaging, Video sequences BibRef

Xu, J., Song, L., Xie, R.,
Two-stream deep encoder-decoder architecture for fully automatic video object segmentation,
VCIP17(1-4)
IEEE DOI 1804
image segmentation, image sequences, learning (artificial intelligence), video signal processing, motion segmentation BibRef

Sun, L.[Lu], Décombas, M.[Marc], Lang, J.[Jochen],
Video Object Segmentation for Content-Aware Video Compression,
CRV16(116-123)
IEEE DOI 1612
BibRef

Bosch, M.[Marc], Li, G.[Guiqin], Wang, K.[Kai],
A two-stage video object segmentation using motion and color information,
ICIP15(3916-3920)
IEEE DOI 1512
object segmentation, video segmentation, video summary BibRef

Wu, Z.Y.[Zheng-Yang], Li, F.[Fuxin], Sukthankar, R.[Rahul], Rehg, J.M.[James M.],
Robust video segment proposals with painless occlusion handling,
CVPR15(4194-4203)
IEEE DOI 1510
BibRef

Fragkiadaki, K.[Katerina], Arbelaez, P.[Pablo], Felsen, P.[Panna], Malik, J.[Jitendra],
Learning to segment moving objects in videos,
CVPR15(4083-4090)
IEEE DOI 1510
BibRef

Pu, S.T.[Song-Tao], Zha, H.B.[Hong-Bin],
Streaming video object segmentation with the adaptive coherence factor,
ICIP13(4235-4238)
IEEE DOI 1402
Video object segmentation BibRef

Meuel, H.[Holger], Reso, M.[Matthias], Jachalsky, J.[Jorn], Ostermann, J.[Jorn],
Superpixel-based segmentation of moving objects for low bitrate ROI coding systems,
AVSS13(395-400)
IEEE DOI 1311
Bandwidth BibRef

Zhang, D.[Dong], Javed, O.[Omar], Shah, M.[Mubarak],
Video Object Co-segmentation by Regulated Maximum Weight Cliques,
ECCV14(VII: 551-566).
Springer DOI 1408
BibRef
Earlier:
Video Object Segmentation through Spatially Accurate and Temporally Dense Extraction of Primary Object Regions,
CVPR13(628-635)
IEEE DOI 1309
Object Segmentation, Video Segmentation BibRef

Xiang, X.[Xiang], Chang, H.[Hong], Luo, J.B.[Jie-Bo],
Online Web-Data-Driven Segmentation of Selected Moving Objects in Videos,
ACCV12(II:134-146).
Springer DOI 1304
BibRef

Ellis, L.[Liam], Zografos, V.[Vasileios],
Online Learning for Fast Segmentation of Moving Objects,
ACCV12(II:52-65).
Springer DOI 1304
BibRef

Di, X.F.[Xiao-Fei], Chang, H.[Hong], Chen, X.L.[Xi-Lin],
Multi-layer Spectral Clustering for Video Segmentation,
ACCV12(II:1-12).
Springer DOI 1304
BibRef

Xiong, H.[Hao], Wang, Z.Y.[Zhi-Yong], He, R.J.[Ren-Jie], Feng, D.D.,
Video Object Segmentation with Occlusion Map,
DICTA12(1-7).
IEEE DOI 1303
BibRef

Ma, T.Y.[Tian-Yang], Latecki, L.J.[Longin Jan],
Maximum weight cliques with mutex constraints for video object segmentation,
CVPR12(670-677).
IEEE DOI 1208
BibRef

García, A.[Alvaro], Bescós, J.[Jesús],
Video Object Segmentation Based on Feedback Schemes Guided by a Low-Level Scene Ontology,
ACIVS08(xx-yy).
Springer DOI 0810
BibRef

Mármol, S.B.L.[Salvador B. López], Artner, N.M.[Nicole M.], Ion, A.[Adrian], Kropatsch, W.G.[Walter G.], Beleznai, C.[Csaba],
Video Object Segmentation Using Graphs,
CIARP08(733-740).
Springer DOI 0809
BibRef

Marchadier, J.[Jocelyn], Kropatsch, W.G.[Walter G.], Hanbury, A.[Allan],
The Redundancy Pyramid and Its Application to Segmentation on an Image Sequence,
DAGM04(432-439).
Springer DOI 0505
BibRef

Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Video Semantic Object Segmentation .