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],
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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
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IET-IPR(14), No. 8, 19 June 2020, pp. 1490-1501.
DOI Link
2005
BibRef
Tian, Y.[Yan],
Cheng, G.H.[Guo-Hua],
Gelernter, J.[Judith],
Yu, S.H.[Shi-Hao],
Song, C.[Chao],
Yang, B.L.[Bai-Lin],
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.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
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.H.[Yu-Hui],
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.S.[Guo-Sheng],
Wen, C.Y.[Chang-Yun],
Wang, J.L.[Jian-Liang],
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
Zhang, R.F.[Ru-Feng],
Kong, T.[Tao],
Wang, X.L.[Xin-Long],
You, M.Y.[Ming-Yu],
Mask encoding:
A general instance mask representation for object segmentation,
PR(124), 2022, pp. 108505.
Elsevier DOI
2203
Mask encoding, Instance segmentation, Video instance segmentation
BibRef
Xu, X.[Xun],
Zhang, L.[Le],
Cheong, L.F.[Loong-Fah],
Li, Z.[Zhuwen],
Zhu, C.[Ce],
Learning Clustering for Motion Segmentation,
CirSysVideo(32), No. 3, March 2022, pp. 908-919.
IEEE DOI
2203
Data models, Motion segmentation, Tuning, Deep learning, Trajectory,
Feature extraction, Motion segmentation, deep learning, subspace clustering
BibRef
Balachandran, G.,
Krishnan, J.V.G.[J. Venu Gopala],
Machine learning based video segmentation of moving scene by motion
index using IO detector and shot segmentation,
IVC(122), 2022, pp. 104443.
Elsevier DOI
2205
Video segmentation, Machine learning, Soft voting, Segmentation,
Gray level matrix, Audio transformation
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
Fujitake, M.[Masato],
Sugimoto, A.[Akihiro],
Temporal feature enhancement network with external memory for
live-stream video object detection,
PR(131), 2022, pp. 108847.
Elsevier DOI
2208
BibRef
Earlier:
Temporal Feature Enhancement Network with External Memory for Object
Detection in Surveillance Video,
ICPR21(7684-7691)
IEEE DOI
2105
Video object detection, Video analysis, Object detection.
Visualization, Interpolation, Surveillance, Object detection,
Streaming media, Traffic control, Feature extraction
BibRef
Liu, J.J.[Jia-Jia],
Dai, H.N.[Hong-Ning],
Zhao, G.Y.[Guo-Ying],
Li, B.[Bo],
Zhang, T.Q.[Tian-Qi],
TMVOS: Triplet Matching for Efficient Video Object Segmentation,
SP:IC(107), 2022, pp. 116779.
Elsevier DOI
2208
Video object segmentation, Embedding learning, Triplet matching
BibRef
Xi, Y.[Yue],
Jia, W.J.[Wen-Jing],
Miao, Q.G.[Qi-Guang],
Liu, X.Z.[Xiang-Zeng],
Fan, X.C.[Xiao-Chen],
Li, H.[Hanhui],
FiFoNet: Fine-Grained Target Focusing Network for Object Detection in
UAV Images,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link
2208
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
Wang, M.M.[Meng-Meng],
Mei, J.B.[Jian-Biao],
Liu, L.[Lina],
Tian, G.Z.[Guan-Zhong],
Liu, Y.[Yong],
Pan, Z.S.[Zai-Sheng],
Delving Deeper Into Mask Utilization in Video Object Segmentation,
IP(31), 2022, pp. 6255-6266.
IEEE DOI
2210
Task analysis, Target tracking, Object segmentation, Decoding,
Visualization, Video sequences, Training,
mask-enhanced matcher
BibRef
Fang, F.[Fen],
Xu, Q.L.[Qian-Li],
Cheng, Y.[Yi],
Sun, Y.[Ying],
Lim, J.H.[Joo-Hwee],
Image Understanding With Reinforcement Learning: Auto-Tuning Image
Attributes and Model Parameters for Object Detection and Segmentation,
CirSysVideo(32), No. 10, October 2022, pp. 6671-6685.
IEEE DOI
2210
Mathematical models, Object detection, Task analysis,
Adaptation models, Training, Tuning, Image segmentation, multi-branch learning
BibRef
Xu, C.[Chao],
Zhang, J.N.[Jiang-Ning],
Wang, M.M.[Meng-Meng],
Tian, G.Z.[Guan-Zhong],
Liu, Y.[Yong],
Multilevel Spatial-Temporal Feature Aggregation for Video Object
Detection,
CirSysVideo(32), No. 11, November 2022, pp. 7809-7820.
IEEE DOI
2211
Feature extraction, Proposals, Object detection, Optical flow,
Detectors, Aggregates, Tracking, Video object detection,
instance ID constraint
BibRef
Gao, M.Q.[Ming-Qi],
Han, J.G.[Jun-Gong],
Zheng, F.[Feng],
Yu, J.J.Q.[James J.Q.],
Montana, G.[Giovanni],
Video Object Segmentation using Point-based Memory Network,
PR(134), 2023, pp. 109073.
Elsevier DOI
2212
Video object segmentation, Point-based feature matching,
Adaptive matching module
BibRef
Guo, P.[Pinxue],
Zhang, W.[Wei],
Li, X.Q.[Xiao-Qiang],
Zhang, W.Q.[Wen-Qiang],
Adaptive Online Mutual Learning Bi-Decoders for Video Object
Segmentation,
IP(31), 2022, pp. 7063-7077.
IEEE DOI
2212
Feature extraction, Adaptation models, Video sequences, Training,
Predictive models, Task analysis, Object segmentation,
bi-decoders mutual learning
BibRef
Qi, Q.[Qiang],
Wang, X.[Xiao],
Hou, T.X.[Tian-Xiang],
Yan, Y.[Yan],
Wang, H.Z.[Han-Zi],
FastVOD-Net: A Real-Time and High-Accuracy Video Object Detector,
ITS(23), No. 11, November 2022, pp. 20926-20942.
IEEE DOI
2212
Object detection, Streaming media, Feature extraction,
Real-time systems, Detectors, Task analysis, Semantics,
real-time detection
BibRef
Huang, P.H.[Peng-Hui],
Xia, X.G.[Xiang-Gen],
Wang, L.Y.[Ling-Yu],
Liu, X.Z.[Xing-Zhao],
Liao, G.S.[Gui-Sheng],
A Coherent Integration Method for Moving Target Detection in a
Parameter Jittering Radar System Based on Signum Coding,
SPLetters(29), 2022, pp. 2313-2317.
IEEE DOI
2212
Radar, Radar cross-sections, Harmonic analysis,
Time-frequency analysis, Radar countermeasures, Couplings,
nonuniform sampling
BibRef
Chen, P.Y.[Ping-Yang],
Hsieh, J.W.[Jun-Wei],
Gochoo, M.[Munkhjargal],
Chen, Y.S.[Yong-Sheng],
Mixed Stage Partial Network and Background Data Augmentation for
Surveillance Object Detection,
ITS(23), No. 12, December 2022, pp. 23533-23547.
IEEE DOI
2212
BibRef
Earlier:
Light-Weight Mixed Stage Partial Network for Surveillance Object
Detection with Background Data Augmentation,
ICIP21(3333-3337)
IEEE DOI
2201
Feature extraction, Object detection, Detectors, Roads,
Vehicle detection, Benchmark testing, Videos, MSPNet, autonomous driving.
Roads, Surveillance, Image processing, Computational efficiency, MSPNet,
background subtraction
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
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
Seong, H.J.[Hong-Je],
Hyun, J.[Junhyuk],
Kim, E.T.[Eun-Tai],
Video Object Segmentation Using Kernelized Memory Network With
Multiple Kernels,
PAMI(45), No. 2, February 2023, pp. 2595-2612.
IEEE DOI
2301
BibRef
Earlier:
Kernelized Memory Network for Video Object Segmentation,
ECCV20(XXII:629-645).
Springer DOI
2011
Kernel, Correlation, Automobiles, Training, Task analysis,
Object segmentation, Image segmentation, hide-and-seek
BibRef
Seong, H.J.[Hong-Je],
Oh, S.W.[Seoung Wug],
Lee, J.Y.[Joon-Young],
Lee, S.W.[Seong-Won],
Lee, S.[Suhyeon],
Kim, E.T.[Eun-Tai],
Hierarchical Memory Matching Network for Video Object Segmentation,
ICCV21(12869-12878)
IEEE DOI
2203
Codes, Memory management, Semantics, Hidden Markov models,
Object segmentation, Benchmark testing, Motion and tracking,
grouping and shape
BibRef
Yan, L.B.[Long-Bin],
Qin, Y.[Yunxiao],
Chen, J.[Jie],
Scale-Balanced Real-Time Object Detection With Varying Input-Image
Resolution,
CirSysVideo(33), No. 1, January 2023, pp. 242-256.
IEEE DOI
2301
Feature extraction, Detectors, Head, Image resolution, Task analysis,
Semantics, Object detection,
multi-scale features fusion
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
Zhou, Q.Y.[Qian-Yu],
Li, X.T.[Xiang-Tai],
He, L.[Lu],
Yang, Y.[Yibo],
Cheng, G.L.[Guang-Liang],
Tong, Y.[Yunhai],
Ma, L.Z.[Li-Zhuang],
Tao, D.C.[Da-Cheng],
TransVOD: End-to-End Video Object Detection With Spatial-Temporal
Transformers,
PAMI(45), No. 6, June 2023, pp. 7853-7869.
IEEE DOI
2305
Transformers, Object detection, Pipelines, Detectors,
Streaming media, Fuses, Task analysis, Video object detection,
video understanding
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
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
Hashmi, K.A.[Khurram Azeem],
Pagani, A.[Alain],
Stricker, D.[Didier],
Afzal, M.Z.[Muhammad Zeshan],
BoxMask: Revisiting Bounding Box Supervision for Video Object
Detection,
WACV23(2029-2039)
IEEE DOI
2302
Location awareness, Upper bound, Codes, Annotations,
Object detection, Detectors, visual reasoning
BibRef
Chen, M.H.[Mei-Hong],
Lang, J.[Jochen],
TemporalNet: Real-time 2D-3D Video Object Detection,
CRV22(205-212)
IEEE DOI
2301
Training, Convolution, Object detection, Detectors, Streaming media,
Network architecture, video processing, object detetction, temporal relation
BibRef
Pourganjalikhan, A.[Ali],
Poullis, C.[Charalambos],
Adaptive Memory Management for Video Object Segmentation,
CRV22(75-82)
IEEE DOI
2301
Adaptive systems, Memory management, Object segmentation, Streaming media,
Indexes, Task analysis, Robots, object tracking, adaptive memory management
BibRef
Fürst, M.[Michael],
Bhugra, P.[Priyash],
Schuster, R.[René],
Stricker, D.[Didier],
Object Permanence in Object Detection Leveraging Temporal Priors at
Inference Time,
ICPR22(3457-3463)
IEEE DOI
2212
Use predictions from previous frame.
Training, Feedback loop, Computational modeling, Training data,
Object detection, Detectors, Particle filters
BibRef
Yang, J.[Jie],
Xia, M.[Mingfu],
Zhou, X.[Xue],
Context-aware Deformable Alignment for Video Object Segmentation,
ICPR22(303-309)
IEEE DOI
2212
Deformable models, Object segmentation, Benchmark testing,
Robustness, Spatiotemporal phenomena, Object tracking
BibRef
Yu, Z.J.[Zhong-Jie],
Wang, G.[Gaoang],
Chen, L.[Lin],
Raschka, S.[Sebastian],
Luo, J.B.[Jie-Bo],
When Few-Shot Learning Meets Video Object Detection,
ICPR22(2986-2992)
IEEE DOI
2212
Deep learning, Annotations, Object detection, Detectors,
Benchmark testing, Videos
BibRef
Chen, X.S.[Xue-Song],
Shi, S.S.[Shao-Shuai],
Zhu, B.[Benjin],
Cheung, K.C.[Ka Chun],
Xu, H.[Hang],
Li, H.S.[Hong-Sheng],
MPPNet: Multi-frame Feature Intertwining with Proxy Points for 3D
Temporal Object Detection,
ECCV22(VIII:680-697).
Springer DOI
2211
BibRef
Zhao, Y.[Yue],
Krähenbühl, P.[Philipp],
Real-Time Online Video Detection with Temporal Smoothing Transformers,
ECCV22(XXXIV:485-502).
Springer DOI
2211
BibRef
Wang, H.[Han],
Tang, J.[Jun],
Liu, X.D.[Xiao-Dong],
Guan, S.[Shanyan],
Xie, R.[Rong],
Song, L.[Li],
PTSEFormer: Progressive Temporal-Spatial Enhanced TransFormer Towards
Video Object Detection,
ECCV22(VIII:732-747).
Springer DOI
2211
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
Saxena, P.[Prafulla],
Biradar, K.[Kuldeep],
Tyagi, D.K.[Dinesh Kumar],
Vipparthi, S.K.[Santosh Kumar],
RIChEx: A Robust Inter-Frame Change Exposure for Segmenting Moving
Objects,
ICIP22(2172-2176)
IEEE DOI
2211
Training, Image segmentation, Motion segmentation,
Object segmentation, Feature extraction, Video surveillance, GAN
BibRef
Yu, Y.[Ye],
Yuan, J.L.[Jia-Lin],
Mittal, G.[Gaurav],
Fuxin, L.[Li],
Chen, M.[Mei],
BATMAN: Bilateral Attention Transformer in Motion-Appearance
Neighboring Space for Video Object Segmentation,
ECCV22(XXIX:612-629).
Springer DOI
2211
BibRef
Liu, Y.[Yong],
Yu, R.[Ran],
Wang, J.H.[Jia-Hao],
Zhao, X.Y.[Xin-Yuan],
Wang, Y.T.[Yi-Tong],
Tang, Y.S.[Yan-Song],
Yang, Y.J.[Yu-Jiu],
Global Spectral Filter Memory Network for Video Object Segmentation,
ECCV22(XXIX:648-665).
Springer DOI
2211
BibRef
Vujasinovic, S.[Stéphane],
Bullinger, S.[Sebastian],
Becker, S.[Stefan],
Scherer-Negenborn, N.[Norbert],
Arens, M.[Michael],
Stiefelhagen, R.[Rainer],
Revisiting Click-Based Interactive Video Object Segmentation,
ICIP22(2756-2760)
IEEE DOI
2211
Measurement, Image segmentation, Pipelines, Object segmentation,
Image segmentation, Interactive systems
BibRef
Cho, S.[Suhwan],
Lee, H.[Heansung],
Lee, M.[Minhyeok],
Park, C.[Chaewon],
Jang, S.J.[Sung-Jun],
Kim, M.J.[Min-Jung],
Lee, S.Y.[Sang-Youn],
Tackling Background Distraction in Video Object Segmentation,
ECCV22(XXII:446-462).
Springer DOI
2211
BibRef
Liu, Y.[Yong],
Yu, R.[Ran],
Yin, F.[Fei],
Zhao, X.Y.[Xin-Yuan],
Zhao, W.[Wei],
Xia, W.H.[Wei-Hao],
Yang, Y.[Yujiu],
Learning Quality-aware Dynamic Memory for Video Object Segmentation,
ECCV22(XXIX:468-486).
Springer DOI
2211
BibRef
Arrigoni, F.[Federica],
Menapace, W.[Willi],
Benkner, M.S.[Marcel Seelbach],
Ricci, E.[Elisa],
Golyanik, V.[Vladislav],
Quantum Motion Segmentation,
ECCV22(XXIX:506-523).
Springer DOI
2211
BibRef
Hu, H.Z.[Han-Zhe],
Chen, Y.[Yinbo],
Xu, J.R.[Jia-Rui],
Borse, S.[Shubhankar],
Cai, H.[Hong],
Porikli, F.M.[Fatih M.],
Wang, X.L.[Xiao-Long],
Learning Implicit Feature Alignment Function for Semantic Segmentation,
ECCV22(XXIX:487-505).
Springer DOI
2211
BibRef
Cheng, H.K.[Ho Kei],
Schwing, A.G.[Alexander G.],
XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin
Memory Model,
ECCV22(XXVIII:640-658).
Springer DOI
2211
BibRef
Wang, Q.[Qiuyue],
Zhang, S.Y.[Song-Yang],
He, X.M.[Xu-Ming],
Robust Temporally-Coherent Strategy for Few-shot Video Instance
Segmentation,
ICIP22(251-255)
IEEE DOI
2211
Image segmentation, Adaptation models, Image coding,
Motion segmentation, Benchmark testing, Robustness, Task analysis,
Few-shot Learning
BibRef
Pan, J.[Jing],
Du, K.[Kaiwen],
Yan, Y.[Yan],
Wang, H.Z.[Han-Zi],
Dualfeat: Dual Feature Aggregation for Video Object Detection,
ICIP22(2901-2905)
IEEE DOI
2211
Dams, Object detection, Streaming media, Feature extraction,
Robustness, Real-time systems, Object tracking, object tracking
BibRef
Liang, J.[Jun],
Chen, H.[Haosheng],
Yan, Y.[Yan],
Lu, Y.[Yang],
Wang, H.Z.[Han-Zi],
Guided Sampling Based Feature Aggregation for Video Object Detection,
ICIP22(1116-1120)
IEEE DOI
2211
Aggregates, Video sequences, Object detection, Feature extraction,
Boosting, Proposals, Task analysis, Video Object Detection, Sampling Strategy
BibRef
Li, X.[Xiangtai],
Zhang, W.W.[Wen-Wei],
Pang, J.M.[Jiang-Miao],
Chen, K.[Kai],
Cheng, G.L.[Guang-Liang],
Tong, Y.[Yunhai],
Loy, C.C.[Chen Change],
Video K-Net: A Simple, Strong, and Unified Baseline for Video
Segmentation,
CVPR22(18825-18835)
IEEE DOI
2210
Image segmentation, Image analysis, Shape, Fuses, Machine vision,
Semantics, Pipelines, Scene analysis and understanding,
Vision applications and systems
BibRef
Yang, J.R.[Jin-Rong],
Liu, S.T.[Song-Tao],
Li, Z.[Zeming],
Li, X.P.[Xiao-Ping],
Sun, J.[Jian],
Real-time Object Detection for Streaming Perception,
CVPR22(5375-5385)
IEEE DOI
2210
Measurement, Detectors, Streaming media, Market research,
Search problems, Real-time systems, Pattern recognition,
Navigation and autonomous driving
BibRef
Botach, A.[Adam],
Zheltonozhskii, E.[Evgenii],
Baskin, C.[Chaim],
End-to-End Referring Video Object Segmentation with Multimodal
Transformers,
CVPR22(4975-4985)
IEEE DOI
2210
Computational modeling, Pipelines, Object segmentation,
Predictive models, Benchmark testing, Transformers,
Video analysis and understanding
BibRef
Wu, J.N.[Jian-Nan],
Jiang, Y.[Yi],
Sun, P.[Peize],
Yuan, Z.H.[Ze-Huan],
Luo, P.[Ping],
Language as Queries for Referring Video Object Segmentation,
CVPR22(4964-4974)
IEEE DOI
2210
Convolution, Pipelines, Object segmentation, Transformers,
Information filters, Pattern recognition, Vision+language,
Video analysis and understanding
BibRef
Xu, K.[Kai],
Yao, A.[Angela],
Accelerating Video Object Segmentation with Compressed Video,
CVPR22(1332-1341)
IEEE DOI
2210
Analytical models, Tracking, Shape, Motion segmentation,
Computational modeling, Redundancy, Segmentation,
Video analysis and understanding
BibRef
Park, K.Y.[Kwan-Yong],
Woo, S.[Sanghyun],
Oh, S.W.[Seoung Wug],
Kweon, I.S.[In So],
Lee, J.Y.[Joon-Young],
Per-Clip Video Object Segmentation,
CVPR22(1342-1351)
IEEE DOI
2210
Training, Correlation, Tracking, Shape, Memory management,
Object segmentation, grouping and shape analysis,
Segmentation
BibRef
Lin, Z.H.[Zhi-Hui],
Yang, T.[Tianyu],
Li, M.[Maomao],
Wang, Z.[Ziyu],
Yuan, C.[Chun],
Jiang, W.H.[Wen-Hao],
Liu, W.[Wei],
SWEM: Towards Real-Time Video Object Segmentation with Sequential
Weighted Expectation-Maximization,
CVPR22(1352-1362)
IEEE DOI
2210
Shape, Computational modeling, Redundancy, Object segmentation,
Streaming media, Feature extraction, Segmentation,
Video analysis and understanding
BibRef
Li, M.X.[Ming-Xing],
Hu, L.[Li],
Xiong, Z.W.[Zhi-Wei],
Zhang, B.[Bang],
Pan, P.[Pan],
Liu, D.[Dong],
Recurrent Dynamic Embedding for Video Object Segmentation,
CVPR22(1322-1331)
IEEE DOI
2210
Training, Codes, Shape, Memory management, Object segmentation,
Maintenance engineering, grouping and shape analysis, Segmentation
BibRef
Pan, W.W.[Wen-Wen],
Shi, H.[Haonan],
Zhao, Z.[Zhou],
Zhu, J.[Jieming],
He, X.[Xiuqiang],
Pan, Z.[Zhigeng],
Gao, L.[Lianli],
Yu, J.[Jun],
Wu, F.[Fei],
Tian, Q.[Qi],
Wnet: Audio-Guided Video Object Segmentation via Wavelet-Based Cross-
Modal Denoising Networks,
CVPR22(1310-1321)
IEEE DOI
2210
Visualization, Frequency-domain analysis, Semantics,
Noise reduction, Video sequences, Object segmentation, Vision + X
BibRef
Bao, Z.P.[Zhi-Peng],
Tokmakov, P.[Pavel],
Jabri, A.[Allan],
Wang, Y.X.[Yu-Xiong],
Gaidon, A.[Adrien],
Hebert, M.[Martial],
Discovering Objects that Can Move,
CVPR22(11779-11788)
IEEE DOI
2210
Representation learning, Learning systems, Tracking, Shape,
Motion segmentation, Dynamics, Segmentation,
Self- semi- meta- Video analysis and understanding
BibRef
Ulker, B.[Berk],
Stuijk, S.[Sander],
Corporaal, H.[Henk],
Wijnhoven, R.[Rob],
Accelerating Video Object Detection by Exploiting Prior Object
Locations,
CIAP22(II:657-668).
Springer DOI
2205
BibRef
Cui, Y.M.[Yi-Ming],
Yan, L.Q.[Li-Qi],
Cao, Z.W.[Zhi-Wen],
Liu, D.F.[Dong-Fang],
TF-Blender: Temporal Feature Blender for Video Object Detection,
ICCV21(8118-8127)
IEEE DOI
2203
Image segmentation, Codes, Object detection, Benchmark testing,
Feature extraction, Task analysis,
BibRef
Chen, S.[Shoufa],
Sun, P.[Peize],
Xie, E.[Enze],
Ge, C.J.[Chong-Jian],
Wu, J.[Jiannan],
Ma, L.[Lan],
Shen, J.J.[Jia-Jun],
Luo, P.[Ping],
Watch Only Once: An End-to-End Video Action Detection Framework,
ICCV21(8158-8167)
IEEE DOI
2203
Location awareness, Computational modeling, Pipelines, Detectors,
Predictive models, Feature extraction,
BibRef
Li, K.[Kejie],
de Tone, D.[Daniel],
Chen, S.[Steven],
Vo, M.[Minh],
Reid, I.D.[Ian D.],
Rezatofighi, H.[Hamid],
Sweeney, C.[Chris],
Straub, J.[Julian],
Newcombe, R.[Richard],
ODAM: Object Detection, Association, and Mapping using Posed RGB
Video,
ICCV21(5978-5988)
IEEE DOI
2203
Point cloud compression, Location awareness, Geometry,
Image color analysis, Volume measurement, Object detection, Stereo,
Detection and localization in 2D and 3D
BibRef
Yang, C.[Charig],
Lamdouar, H.[Hala],
Lu, E.[Erika],
Zisserman, A.[Andrew],
Xie, W.[Weidi],
Self-supervised Video Object Segmentation by Motion Grouping,
ICCV21(7157-7168)
IEEE DOI
2203
Annotations, Motion segmentation, Scalability, Object segmentation,
Manuals, Benchmark testing, Segmentation, grouping and shape,
Video analysis and understanding
BibRef
Wang, W.Y.[Wei-Yao],
Feiszli, M.[Matt],
Wang, H.[Heng],
Tran, D.[Du],
Unidentified Video Objects:
A Benchmark for Dense, Open-World Segmentation,
ICCV21(10756-10765)
IEEE DOI
2203
Training, Annotations, Motion segmentation, Computational modeling,
Object segmentation, Object detection, Datasets and evaluation,
Video analysis and understanding
BibRef
Ji, G.P.[Ge-Peng],
Fu, K.[Keren],
Wu, Z.[Zhe],
Fan, D.P.[Deng-Ping],
Shen, J.B.[Jian-Bing],
Shao, L.[Ling],
Full-Duplex Strategy for Video Object Segmentation,
ICCV21(4902-4913)
IEEE DOI
2203
Upper bound, Purification, Full-duplex system, Object segmentation,
Object detection, Transformers, Robustness,
Low-level and physics-based vision
BibRef
Zhang, Y.Z.[Yi-Zhe],
Borse, S.[Shubhankar],
Cai, H.[Hong],
Wang, Y.[Ying],
Bi, N.[Ning],
Jiang, X.Y.[Xiao-Yun],
Porikli, F.M.[Fatih M.],
Perceptual Consistency in Video Segmentation,
WACV22(2623-2632)
IEEE DOI
2202
Training, Image segmentation,
Measurement uncertainty, Semantics, Predictive models,
Grouping and Shape Scene Understanding
BibRef
Schmidt, C.[Christian],
Athar, A.[Ali],
Mahadevan, S.[Sabarinath],
Leibe, B.[Bastian],
D2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in
Videos,
WACV22(1929-1938)
IEEE DOI
2202
Convolutional codes, Image segmentation,
Object segmentation, Scene Understanding
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
Azulay, A.[Aharon],
Halperin, T.[Tavi],
Vantzos, O.[Orestis],
Bornstein, N.[Nadav],
Bibi, O.[Ofir],
Temporally stable video segmentation without video annotations,
WACV22(1919-1928)
IEEE DOI
2202
Training, Optical filters, Image segmentation, Adaptation models,
Current measurement, Image annotation,
Grouping and Shape Deep Learning
BibRef
Cho, S.[Suhwan],
Lee, H.[Heansung],
Kim, M.[Minjung],
Jang, S.J.[Sung-Jun],
Lee, S.Y.[Sang-Youn],
Pixel-Level Bijective Matching for Video Object Segmentation,
WACV22(1453-1462)
IEEE DOI
2202
Codes, Object segmentation, Benchmark testing, Optimal matching,
Vision for Robotics
BibRef
Yang, F.[Fan],
Karanam, S.[Srikrishna],
Zheng, M.[Meng],
Chen, T.[Terrence],
Ling, H.B.[Hai-Bin],
Wu, Z.[Ziyan],
Multi-motion and Appearance Self-Supervised Moving Object Detection,
WACV22(2101-2110)
IEEE DOI
2202
Training, Image coding, Aggregates,
Object detection, Cameras, Encoding,
Semi- and Un- supervised Learning
BibRef
Tschernezki, V.[Vadim],
Larlus, D.[Diane],
Vedaldi, A.[Andrea],
NeuralDiff: Segmenting 3D objects that move in egocentric videos,
3DV21(910-919)
IEEE DOI
2201
Motion segmentation, Dynamics, Video sequences, Neural networks,
Object segmentation, Rendering (computer graphics)
BibRef
Besbinar, B.[Beril],
Frossard, P.[Pascal],
Self-Supervision By Prediction for Object Discovery In Videos,
ICIP21(1509-1513)
IEEE DOI
2201
Deep learning, Annotations, Heuristic algorithms, Pipelines,
Dynamics, Predictive models, Self-supervision, video prediction,
unsupervised scene decomposition
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
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.Z.[Hao-Zhe],
Yao, H.X.[Hong-Xun],
Zhou, S.C.[Shang-Chen],
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.X.[Nan-Xuan],
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, 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
Korkmaz, C.[Cansu],
Tekalp, A.M.[A. Murat],
Dogan, Z.[Zafer],
Erdem, E.[Erkut],
Erdem, A.[Aykut],
Perception-Distortion Trade-Off in the SR Space Spanned by Flow
Models,
ICIP22(2396-2400)
IEEE DOI
2211
Measurement, Visualization, Superresolution, Aerospace electronics,
Task analysis, normalizing flows, super-resolution,
perception-distortion trade-off
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
Xu, M.Z.[Mu-Zhou],
Zhong, S.[Shan],
Liu, C.P.[Chun-Ping],
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
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.Q.[Gui-Qin],
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 .