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, 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
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
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.[Yiran],
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
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
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
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
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
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
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 .