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
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
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
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
Liu, W.D.[Wei-De],
Lin, G.S.[Guo-Sheng],
Zhang, T.Y.[Tian-Yi],
Liu, Z.C.[Zi-Chuan],
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
Zhu, W.C.[Wen-Cheng],
Li, J.H.[Jia-Hao],
Lu, J.W.[Ji-Wen],
Zhou, J.[Jie],
Separable Structure Modeling for Semi-Supervised Video Object
Segmentation,
CirSysVideo(32), No. 1, January 2022, pp. 330-344.
IEEE DOI
2201
Object segmentation, Feature extraction, Target tracking,
Data models, Object tracking, Video sequences, Task analysis,
semi-supervised learning
BibRef
Giraldo, J.H.[Jhony H.],
Javed, S.[Sajid],
Bouwmans, T.[Thierry],
Graph Moving Object Segmentation,
PAMI(44), No. 5, May 2022, pp. 2485-2503.
IEEE DOI
2204
Videos, Task analysis, Signal processing algorithms,
Object segmentation, Semisupervised learning, Deep learning,
video object segmentation
BibRef
En, Q.[Qing],
Duan, L.J.[Li-Juan],
Zhang, Z.X.[Zhao-Xiang],
Joint Multisource Saliency and Exemplar Mechanism for Weakly
Supervised Video Object Segmentation,
IP(30), 2021, pp. 8155-8169.
IEEE DOI
2110
Spatiotemporal phenomena, Feature extraction,
Motion segmentation, Annotations, Training, Task analysis,
spatiotemporal saliency
BibRef
Xi, L.[Lin],
Chen, W.H.[Wei-Hai],
Wu, X.M.[Xing-Ming],
Liu, Z.[Zhong],
Li, Z.G.[Zheng-Guo],
Implicit Motion-Compensated Network for Unsupervised Video Object
Segmentation,
CirSysVideo(32), No. 9, September 2022, pp. 6279-6292.
IEEE DOI
2209
Feature extraction, Motion compensation, Optical flow, Correlation,
Object segmentation, Finite element analysis, Video sequences,
motion compensation
BibRef
Xi, L.[Lin],
Chen, W.H.[Wei-Hai],
Wu, X.M.[Xing-Ming],
Liu, Z.[Zhong],
Li, Z.G.[Zheng-Guo],
Online Unsupervised Video Object Segmentation via Contrastive Motion
Clustering,
CirSysVideo(34), No. 2, February 2024, pp. 995-1006.
IEEE DOI Code:
WWW Link.
2402
Motion segmentation, Optical flow, Streaming media, Prototypes, Optimization,
Object segmentation, Clustering algorithms, clustering methods
BibRef
Lin, F.C.[Fan-Chao],
Xie, H.T.[Hong-Tao],
Liu, C.B.[Chuan-Bin],
Zhang, Y.D.[Yong-Dong],
Bilateral Temporal Re-Aggregation for Weakly-Supervised Video Object
Segmentation,
CirSysVideo(32), No. 7, July 2022, pp. 4498-4512.
IEEE DOI
2207
Task analysis, Object segmentation, Target tracking,
Benchmark testing, Aggregates, Training, Reliability,
weakly-supervised prediction
BibRef
Zhou, Y.F.[Yi-Feng],
Xu, X.[Xing],
Shen, F.M.[Fu-Min],
Zhu, X.F.[Xiao-Feng],
Shen, H.T.[Heng Tao],
Flow-Edge Guided Unsupervised Video Object Segmentation,
CirSysVideo(32), No. 12, December 2022, pp. 8116-8127.
IEEE DOI
2212
Motion segmentation, Feature extraction, Object segmentation,
Image edge detection, Deep learning, Image segmentation, deep learning
BibRef
Li, Y.X.[Yu-Xi],
Xu, N.[Ning],
Yang, W.J.[Wen-Jie],
See, J.[John],
Lin, W.Y.[Wei-Yao],
Exploring the Semi-Supervised Video Object Segmentation Problem from a
Cyclic Perspective,
IJCV(130), No. 10, October 2022, pp. 2408-2424.
Springer DOI
2209
BibRef
Fan, J.Q.[Jia-Qing],
Liu, B.[Bo],
Zhang, K.[Kaihua],
Liu, Q.S.[Qing-Shan],
Semi-Supervised Video Object Segmentation via Learning Object-Aware
Global-Local Correspondence,
CirSysVideo(32), No. 12, December 2022, pp. 8153-8164.
IEEE DOI
2212
Adaptation models, Benchmark testing, Object segmentation,
Deep learning, Semantics, Semi-supervised learning
BibRef
Haller, E.[Emanuela],
Florea, A.M.[Adina Magda],
Leordeanu, M.[Marius],
Iterative Knowledge Exchange Between Deep Learning and Space-Time
Spectral Clustering for Unsupervised Segmentation in Videos,
PAMI(44), No. 11, November 2022, pp. 7638-7656.
IEEE DOI
2210
Videos, Clustering algorithms, Task analysis, Object segmentation,
Mathematical models, Deep learning, Convergence, deep learning
BibRef
Burceanu, E.[Elena],
Leordeanu, M.[Marius],
Learning a fast 3D spectral approach to object segmentation and
tracking over space and time,
AI(340), 2025, pp. 104281.
Elsevier DOI
2502
Video object segmentation, Tracking, Spectral clustering,
Power iteration, 3D convolution, Graph optimization
BibRef
Marcu, A.[Alina],
Licaret, V.[Vlad],
Costea, D.[Dragos],
Leordeanu, M.[Marius],
Semantics Through Time: Semi-supervised Segmentation of Aerial Videos
with Iterative Label Propagation,
ACCV20(I:537-552).
Springer DOI
2103
BibRef
Muthu, S.[Sundaram],
Tennakoon, R.[Ruwan],
Rathnayake, T.[Tharindu],
Hoseinnezhad, R.[Reza],
Suter, D.[David],
Bab-Hadiashar, A.[Alireza],
Generalized framework for image and video object segmentation using
affinity learning and message passing GNNS,
CVIU(236), 2023, pp. 103812.
Elsevier DOI
2310
Unsupervised video object segmentation, Image segmentation,
Lifted multi-cuts, Graph neural networks, Affinity learning
BibRef
Lan, M.[Meng],
Zhang, J.[Jing],
Wang, Z.[Zengmao],
Coherence-aware context aggregator for fast video object segmentation,
PR(136), 2023, pp. 109214.
Elsevier DOI
2301
Video object segmentation, Semi-supervised learning,
Spatio-temporal representation, Context
BibRef
Sun, J.[Jiadai],
Mao, Y.X.[Yu-Xin],
Dai, Y.C.[Yu-Chao],
Zhong, Y.R.[Yi-Ran],
Wang, J.Y.[Jian-Yuan],
MUNet: Motion uncertainty-aware semi-supervised video object
segmentation,
PR(138), 2023, pp. 109399.
Elsevier DOI
2303
Video object segmentation, Uncertainty, Motion estimation, Self-supervised
BibRef
Chen, Y.D.[Ya-Dang],
Ji, C.J.[Chuan-Jun],
Yang, Z.X.[Zhi-Xin],
Wu, E.[Enhua],
Spatial constraint for efficient semi-supervised video object
segmentation,
CVIU(237), 2023, pp. 103843.
Elsevier DOI
2311
Video object segmentation, Memory-based methods,
Redundant information, Semantically similar objects
BibRef
Pei, G.S.[Gen-Sheng],
Shen, F.M.[Fu-Min],
Yao, Y.Z.[Ya-Zhou],
Chen, T.[Tao],
Hua, X.S.[Xian-Sheng],
Shen, H.T.[Heng-Tao],
Hierarchical Graph Pattern Understanding for Zero-Shot Video Object
Segmentation,
IP(32), 2023, pp. 5909-5920.
IEEE DOI Code:
WWW Link.
2311
BibRef
Pei, G.S.[Gen-Sheng],
Yao, Y.Z.[Ya-Zhou],
Shen, F.M.[Fu-Min],
Huang, D.[Dan],
Huang, X.G.[Xing-Guo],
Shen, H.T.[Heng-Tao],
Hierarchical Co-Attention Propagation Network for Zero-Shot Video
Object Segmentation,
IP(32), 2023, pp. 2348-2359.
IEEE DOI
2305
Motion segmentation, Optical imaging, Optical propagation,
Adaptive optics, Optical fiber networks, Phase change materials,
cross-modal
BibRef
Tang, Y.[Yin],
Chen, T.[Tao],
Jiang, X.[Xiruo],
Yao, Y.Z.[Ya-Zhou],
Xie, G.S.[Guo-Sen],
Shen, H.T.[Heng-Tao],
Holistic Prototype Attention Network for Few-Shot Video Object
Segmentation,
CirSysVideo(34), No. 8, August 2024, pp. 6699-6709.
IEEE DOI Code:
WWW Link.
2408
Prototypes, Task analysis, Object segmentation,
Semantic segmentation, Semantics, Feature extraction, Annotations,
few-shot semantic segmentation
BibRef
Pei, G.S.[Gen-Sheng],
Shen, F.M.[Fu-Min],
Yao, Y.Z.[Ya-Zhou],
Xie, G.S.[Guo-Sen],
Tang, Z.M.[Zhen-Min],
Tang, J.H.[Jin-Hui],
Hierarchical Feature Alignment Network for Unsupervised Video Object
Segmentation,
ECCV22(XXXIV:596-613).
Springer DOI
2211
BibRef
Chen, Y.D.[Ya-Dang],
Zhang, D.W.[Ding-Wei],
Zheng, Y.H.[Yu-Hui],
Yang, Z.X.[Zhi-Xin],
Wu, E.[Enhua],
Zhao, H.X.[Hai-Xing],
Boosting Video Object Segmentation via Robust and Efficient Memory
Network,
CirSysVideo(34), No. 5, May 2024, pp. 3340-3352.
IEEE DOI
2405
Memory management, Task analysis, Termination of employment,
Redundancy, Feature extraction, Training, Video sequences,
semi-supervised learning
BibRef
Kim, J.[Jiyun],
Kim, J.[JooHo],
Hong, S.[Sungeun],
G-TRACE: Grouped temporal recalibration for video object segmentation,
IVC(147), 2024, pp. 105050.
Elsevier DOI
2406
Semi-supervised video object segmentation, Memory attention,
Hierarchical grouping
BibRef
Li, P.[Ping],
Zhang, Y.[Yu],
Yuan, L.[Li],
Xiao, H.X.[Hua-Xin],
Lin, B.B.[Bin-Bin],
Xu, X.H.[Xiang-Hua],
Efficient Long-Short Temporal Attention Network for Unsupervised
Video Object Segmentation,
PR(146), 2024, pp. 110078.
Elsevier DOI
2311
Unsupervised video object segmentation, Long temporal memory,
Short temporal attention, Efficient projection
BibRef
Han, M.F.[Ming-Fei],
Wang, Y.[Yali],
Li, M.J.[Ming-Jie],
Chang, X.J.[Xiao-Jun],
Yang, Y.[Yi],
Qiao, Y.[Yu],
Progressive Frame-Proposal Mining for Weakly Supervised Video Object
Detection,
IP(33), 2024, pp. 1560-1573.
IEEE DOI
2403
BibRef
Earlier: A1, A2, A4, A6, Only:
Mining Inter-video Proposal Relations for Video Object Detection,
ECCV20(XXI:431-446).
Springer DOI
2011
Proposals, Object detection, Detectors, Annotations, Task analysis,
Training, Benchmark testing, Video object detection,
holistic-view refinement
BibRef
Zhang, Y.Z.[Yun-Zuo],
Yu, P.[Puze],
Xiao, Y.[Yaoge],
Wang, S.S.[Shuang-Shuang],
Pyramid-structured multi-scale transformer for efficient
semi-supervised video object segmentation with adaptive fusion,
PRL(194), 2025, pp. 48-54.
Elsevier DOI
2506
Video object segmentation, Real-time video segmentation, Pyramid structure
BibRef
Yan, K.[Kun],
Wei, F.[Fangyun],
Dai, S.Y.[Shu-Yu],
Wu, M.H.[Ming-Hui],
Wang, P.[Ping],
Xu, C.[Chang],
Low-Shot Video Object Segmentation,
PAMI(47), No. 7, July 2025, pp. 5538-5555.
IEEE DOI
2506
Training, Object segmentation, Data models, Annotations,
Semisupervised learning, Computational modeling, low-shot learning
BibRef
Mahadevan, S.[Sabarinath],
Zulfikar, I.E.[Idil Esen],
Voigtlaender, P.[Paul],
Leibe, B.[Bastian],
Point-VOS: Pointing Up Video Object Segmentation,
CVPR24(22217-22226)
IEEE DOI Code:
WWW Link.
2410
Training, Codes, Annotations, Grounding, Image annotation,
Object segmentation, video object segmentation,
weakly-supervised video object segmentation
BibRef
Mahmud, T.[Tanvir],
Liu, C.H.[Chun-Hao],
Yaman, B.[Burhaneddin],
Marculescu, D.[Diana],
SSVOD: Semi-Supervised Video Object Detection with Sparse Annotations,
WACV24(6759-6768)
IEEE DOI Code:
WWW Link.
2404
Uncertainty, Annotations, Dynamics, Noise, Estimation,
Object detection, Detectors, Algorithms,
Autonomous Driving
BibRef
Su, T.[Tiankang],
Song, H.H.[Hui-Hui],
Liu, D.[Dong],
Liu, B.[Bo],
Liu, Q.S.[Qing-Shan],
Unsupervised Video Object Segmentation with Online Adversarial
Self-Tuning,
ICCV23(688-698)
IEEE DOI
2401
BibRef
Lee, S.[Seunghoon],
Cho, S.[Suhwan],
Lee, D.[Dogyoon],
Lee, M.[Minhyeok],
Lee, S.Y.[Sang-Youn],
Tsanet: Temporal and Scale Alignment for Unsupervised Video Object
Segmentation,
ICIP23(1535-1539)
IEEE DOI
2312
BibRef
Meunier, E.[Etienne],
Bouthemy, P.[Patrick],
Unsupervised Space-Time Network for Temporally-Consistent
Segmentation of Multiple Motions,
CVPR23(22139-22148)
IEEE DOI
2309
BibRef
Ponimatkin, G.[Georgy],
Samet, N.[Nermin],
Xiao, Y.[Yang],
Du, Y.M.[Yu-Ming],
Marlet, R.[Renaud],
Lepetit, V.[Vincent],
A Simple and Powerful Global Optimization for Unsupervised Video
Object Segmentation,
WACV23(5881-5892)
IEEE DOI
2302
Training, Semantics, Object segmentation, Linear programming, Solids,
Standards
BibRef
Cho, S.[Suhwan],
Lee, M.[Minhyeok],
Lee, S.[Seunghoon],
Park, C.[Chaewon],
Kim, D.[Donghyeong],
Lee, S.Y.[Sang-Youn],
Treating Motion as Option to Reduce Motion Dependency in Unsupervised
Video Object Segmentation,
WACV23(5129-5138)
IEEE DOI
2302
Federated learning, Video sequences, Object segmentation,
Benchmark testing, Streaming media, Solids, Real-time systems,
Embedded sensing/real-time techniques
BibRef
Cho, S.[Suhwan],
Lee, M.[Minhyeok],
Lee, S.[Seunghoon],
Lee, D.[Dogyoon],
Choi, H.[Heeseung],
Kim, I.J.[Ig-Jae],
Lee, S.Y.[Sang-Youn],
Dual Prototype Attention for Unsupervised Video Object Segmentation,
CVPR24(19238-19247)
IEEE DOI Code:
WWW Link.
2410
Codes, Attention mechanisms, Motion segmentation, Prototypes,
Collaboration, Object segmentation
BibRef
Lee, M.[Minhyeok],
Cho, S.[Suhwan],
Lee, D.[Dogyoon],
Park, C.[Chaewon],
Lee, J.[Jungho],
Lee, S.Y.[Sang-Youn],
Guided Slot Attention for Unsupervised Video Object Segmentation,
CVPR24(3807-3816)
IEEE DOI Code:
WWW Link.
2410
Filtering, Fuses, Video sequences, Object segmentation,
Nearest neighbor methods, Transformers
BibRef
Lee, M.[Minhyeok],
Cho, S.[Suhwan],
Lee, S.H.[Seung-Hoon],
Park, C.[Chaewon],
Lee, S.Y.[Sang-Youn],
Unsupervised Video Object Segmentation via Prototype Memory Network,
WACV23(5913-5923)
IEEE DOI
2302
Adaptation models, Video sequences, Prototypes,
Object segmentation, Feature extraction, Prediction algorithms,
BibRef
Launay, C.[Claire],
Vacher, J.[Jonathan],
Coen-Cagli, R.[Ruben],
Unsupervised Video Segmentation Algorithms Based On Flexibly
Regularized Mixture Models,
ICIP22(4073-4077)
IEEE DOI
2211
Image segmentation, Uncertainty, Motion segmentation,
Heuristic algorithms, Soft sensors, Dynamics, Mixture models,
Temporal Propagation
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
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
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, Logic gates
BibRef
Zhang, K.[Kaihua],
Zhao, Z.C.[Zi-Cheng],
Liu, D.[Dong],
Liu, Q.S.[Qing-Shan],
Liu, B.[Bo],
Deep Transport Network for Unsupervised Video Object Segmentation,
ICCV21(8761-8770)
IEEE DOI
2203
Training, Measurement, Costs, Fuses, Object segmentation,
Feature extraction,
Video analysis and understanding
BibRef
Shrestha, S.[Sahir],
Armin, M.A.[Mohammad Ali],
Li, H.D.[Hong-Dong],
Barnes, N.M.[Nick M.],
Learning to Segment Dominant Object Motion from Watching Videos,
DICTA21(01-08)
IEEE DOI
2201
Training, Image segmentation, Technological innovation,
Motion segmentation, Computational modeling, Object segmentation,
unsupervised video object segmentation
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
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
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
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
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
Zhang, X.[Xuan],
Han, G.X.[Guang-Xing],
He, W.D.[Wen-Duo],
Unsupervised Feature Propagation for Fast Video Object Detection Using
Generative Adversarial Networks,
MMMod20(I:617-627).
Springer DOI
2003
BibRef
Li, W.J.[Wen-Jing],
Zhang, X.[Xiang],
Hu, Y.J.[Yu-Jie],
Tang, Y.Q.[Ying-Qi],
Mask-ranking Network for Semi-supervised Video Object Segmentation,
ACCV20(I:620-636).
Springer DOI
2103
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
Misra, I.[Ishan],
Shrivastava, A.[Abhinav],
Hebert, M.[Martial],
Watch and learn:
Semi-supervised learning of object detectors from videos,
CVPR15(3593-3602)
IEEE DOI
1510
BibRef
Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Video Semantic Object Segmentation .