19.3.4.2 Video Semantic Object Segmentation

Chapter Contents (Back)
Motion, Detection. Motion Detection. Motion Segmentation. Sequences. Semantic Segmentation. Object Segmentation.
See also Semantic Segmentation, Label and Segment Together.
See also Video Instance Segmentation.

Jiang, J., Song, X.,
An Optimized Higher Order CRF for Automated Labeling and Segmentation of Video Objects,
CirSysVideo(26), No. 3, March 2016, pp. 506-516.
IEEE DOI 1603
Color BibRef

Czúni, L.[László], Rashad, M.[Metwally],
The use of IMUs for video object retrieval in lightweight devices,
JVCIR(48), No. 1, 2017, pp. 30-42.
Elsevier DOI 1708
BibRef
Earlier:
View centered video-based object recognition for lightweight devices,
WSSIP16(1-4)
IEEE DOI 1608
Video object retrieval. image recognition BibRef

Wang, Y.H.[Yu-Hang], Liu, J.[Jing], Li, Y.[Yong], Fu, J.[Jun], Xu, M.[Min], Lu, H.Q.[Han-Qing],
Hierarchically Supervised Deconvolutional Network for Semantic Video Segmentation,
PR(64), No. 1, 2017, pp. 437-445.
Elsevier DOI 1701
Semantic video segmentation BibRef

Zhang, Y.[Yu], Chen, X.W.[Xiao-Wu], Li, J.[Jia], Wang, C.[Chen], Xia, C.Q.[Chang-Qun], Li, J.[Jun],
Semantic Object Segmentation in Tagged Videos via Detection,
PAMI(40), No. 7, July 2018, pp. 1741-1754.
IEEE DOI 1806
Image segmentation, Motion segmentation, Object segmentation, Proposals, Semantics, Spatiotemporal phenomena, Videos, weakly supervised segmentation BibRef

Zhang, Y.[Yu], Chen, X.W.[Xiao-Wu], Li, J.[Jia], Teng, W.[Wei], Song, H.[Haokun],
Exploring Weakly Labeled Images for Video Object Segmentation With Submodular Proposal Selection,
IP(27), No. 9, September 2018, pp. 4245-4259.
IEEE DOI 1807
data mining, image matching, image segmentation, learning (artificial intelligence), video signal processing, weakly labeled video BibRef

Zhang, Y.[Yu], Chen, X.W.[Xiao-Wu], Li, J.[Jia], Wang, C.[Chen], Xia, C.Q.[Chang-Qun],
Semantic object segmentation via detection in weakly labeled video,
CVPR15(3641-3649)
IEEE DOI 1510
BibRef

Zhang, Y.H.[Yin-Hui], He, Z.F.[Zi-Fen],
Agnostic attribute segmentation of dynamic scenes with limited spatio-temporal resolution,
PR(91), 2019, pp. 261-271.
Elsevier DOI 1904
Video object segmentation, Conditional random field, Class-agnostic, Semantic space, Spatio-temporal resolution BibRef

Chen, Y., Hao, C., Liu, A.X., Wu, E.,
Multilevel Model for Video Object Segmentation Based on Supervision Optimization,
MultMed(21), No. 8, August 2019, pp. 1934-1945.
IEEE DOI 1908
image motion analysis, image resolution, image segmentation, optimisation, video signal processing, appearance, motion clues, semantic classification BibRef

Chen, X.[Xin], Wu, A.[Aming], Han, Y.[Yahong],
Capturing the spatio-temporal continuity for video semantic segmentation,
IET-IPR(13), No. 14, 12 December 2019, pp. 2813-2820.
DOI Link 1912
BibRef

Wu, J.[Junrong], Wen, Z.Z.[Zong-Zheng], Zhao, S.[Sanyuan], Huang, K.[Kele],
Video semantic segmentation via feature propagation with holistic attention,
PR(104), 2020, pp. 107268.
Elsevier DOI 2005
Real-time, Attention mechanism, Feature propagation, Video semantic segmentation BibRef

Sharma, V.[Vipul], Mir, R.N.[Roohie Naaz],
SSFNET-VOS: Semantic segmentation and fusion network for video object segmentation,
PRL(140), 2020, pp. 49-58.
Elsevier DOI 2012
Multimedia processing, Video object segmentation, Unsupervised learning, Semantic segmentation BibRef

Zhang, G., Wong, H.C., Lo, S.L.,
Multi-Attention Network for Unsupervised Video Object Segmentation,
SPLetters(28), 2021, pp. 71-75.
IEEE DOI 2101
Logic gates, Object segmentation, Training, Task analysis, Semantics, Decoding, Visualization, Attention, deep networks, unsupervised video object segmentation BibRef

Zhuang, J.F.[Jia-Fan], Wang, Z.L.[Zi-Lei], Wang, B.K.[Bing-Ke],
Video Semantic Segmentation With Distortion-Aware Feature Correction,
CirSysVideo(31), No. 8, August 2021, pp. 3128-3139.
IEEE DOI 2108
Optical distortion, Image segmentation, Semantics, Optical imaging, Distortion, Optical propagation, Feature extraction, feature correction BibRef

Yuan, Y.C.[Yi-Chen], Wang, L.J.[Li-Jun], Wang, Y.F.[Yi-Fan],
CSANet for Video Semantic Segmentation With Inter-Frame Mutual Learning,
SPLetters(28), 2021, pp. 1675-1679.
IEEE DOI 2109
Semantics, Feature extraction, Training, Optical sensors, Image segmentation, Convolution, Context modeling, mutual learning BibRef

Zhang, J.[Jia], Li, W.[Wei], Li, Z.X.[Zhi-Xin],
Distinguishing foreground and background alignment for unsupervised domain adaptative semantic segmentation,
IVC(124), 2022, pp. 104513.
Elsevier DOI 2208
Semantic segmentation, Self-supervised learning, pseudo labels, Attention mechanism, Focal loss BibRef

Wu, W.[Wei], Chu, T.[Tao], Liu, Q.[Qiong],
Complementarity-aware cross-modal feature fusion network for RGB-T semantic segmentation,
PR(131), 2022, pp. 108881.
Elsevier DOI 2208
RGB-T, Cross-modal fusion, Multi-supervision, Semantic segmentation BibRef

Li, R.[Ruoqi], Wang, Y.F.[Yi-Fan], Wang, L.J.[Li-Jun], Lu, H.C.[Hu-Chuan], Wei, X.P.[Xiao-Peng], Zhang, Q.[Qiang],
From Pixels to Semantics: Self-Supervised Video Object Segmentation With Multiperspective Feature Mining,
IP(31), 2022, pp. 5801-5812.
IEEE DOI 2209
Semantics, Training, Feature extraction, Image reconstruction, Task analysis, Object segmentation, Image segmentation, feature mining BibRef

Ye, P.[Peng], Li, B.P.[Bao-Pu], Chen, T.[Tao], Fan, J.Y.[Jia-Yuan], Mei, Z.[Zhen], Lin, C.[Chen], Zuo, C.Y.[Chong-Yan], Chi, Q.H.[Qing-Hua], Ouyang, W.L.[Wan-Li],
Efficient Joint-Dimensional Search with Solution Space Regularization for Real-Time Semantic Segmentation,
IJCV(130), No. 11, November 2022, pp. 2674-2694.
Springer DOI 2210
BibRef

Delibasoglu, I.[Ibrahim], Kosesoy, I.[Irfan], Kotan, M.[Muhammed], Selamet, F.[Feyza],
Motion detection in moving camera videos using background modeling and FlowNet,
JVCIR(88), 2022, pp. 103616.
Elsevier DOI 2210
Motion detection, Moving object detection, Dense optical flow, Moving camera BibRef

Zhang, Y.Z.[Yun-Zuo], Guo, K.[Kaina], Tao, R.[Ran],
Adaptive Spatio-Temporal Tube for Fast Motion Segments Extraction of Videos,
SPLetters(29), 2022, pp. 2308-2312.
IEEE DOI 2212
Videos, Motion segmentation, Electron tubes, Computational complexity, Image segmentation, Data mining, sampling-line adjustment factor BibRef

Li, G.[Gongyang], Wang, Y.[Yike], Liu, Z.[Zhi], Zhang, X.P.[Xin-Peng], Zeng, D.[Dan],
RGB-T Semantic Segmentation With Location, Activation, and Sharpening,
CirSysVideo(33), No. 3, March 2023, pp. 1223-1235.
IEEE DOI 2303
Semantics, Feature extraction, Image segmentation, Decoding, Lighting, Optical fibers, Collaboration, edge sharpening BibRef

Xiong, J.J.[Jing-Jing], Po, L.M.[Lai-Man], Yu, W.Y.[Wing-Yin], Zhao, Y.Z.[Yu-Zhi], Cheung, K.W.[Kwok-Wai],
Distortion Map-Guided Feature Rectification for Efficient Video Semantic Segmentation,
MultMed(25), 2023, pp. 1019-1032.
IEEE DOI 2303
Optical distortion, Semantics, Distortion, Feature extraction, Image analysis, Image segmentation, Optical imaging, optical flow BibRef

Zhou, T.F.[Tian-Fei], Porikli, F.M.[Fatih M.], Crandall, D.J.[David J.], Van Gool, L.J.[Luc J.], Wang, W.G.[Wen-Guan],
A Survey on Deep Learning Technique for Video Segmentation,
PAMI(45), No. 6, June 2023, pp. 7099-7122.
IEEE DOI 2305
Object segmentation, Automobiles, Semantic segmentation, Task analysis, Motion segmentation, Deep learning, Roads, deep learning BibRef

Liang, Z.Y.[Zhi-Yuan], Dai, X.D.[Xiang-Dong], Wu, Y.Q.[Yi-Qian], Jin, X.G.[Xiao-Gang], Shen, J.B.[Jian-Bing],
Multi-Granularity Context Network for Efficient Video Semantic Segmentation,
IP(32), 2023, pp. 3163-3175.
IEEE DOI 2306
Semantics, Semantic segmentation, Prototypes, Aggregates, Feature extraction, Training, Task analysis, non-local operation BibRef

Zhao, S.[Shenlu], Zhang, Q.[Qiang],
A Feature Divide-and-Conquer Network for RGB-T Semantic Segmentation,
CirSysVideo(33), No. 6, June 2023, pp. 2892-2905.
IEEE DOI 2306
Feature extraction, Semantic segmentation, Data mining, Semantics, Lighting, Decoding, Thermal sensors, RGB-T semantic segmentation, multi-scale contextual information BibRef

Mi, A.[Aizhong], Gao, M.M.[Ming-Ming], Huo, Z.Q.[Zhan-Qiang], Qiao, Y.X.[Ying-Xu], Chen, J.[Jian], Jia, H.Y.[Hai-Yang],
Semantics recalibration and detail enhancement network for real-time semantic segmentation,
IET-CV(17), No. 4, 2023, pp. 461-472.
DOI Link 2306
computer vision, image processing, image segmentation, neural net architecture, neural nets BibRef

Sun, M.J.[Ming-Jie], Xiao, J.[Jimin], Lim, E.G.[Eng Gee], Zhao, Y.[Yao],
Starting Point Selection and Multiple-Standard Matching for Video Object Segmentation With Language Annotation,
MultMed(25), 2023, pp. 3354-3363.
IEEE DOI 2309
BibRef

Li, D.[Dianze], Tian, Y.H.[Yong-Hong], Li, J.N.[Jia-Ning],
SODFormer: Streaming Object Detection With Transformer Using Events and Frames,
PAMI(45), No. 11, November 2023, pp. 14020-14037.
IEEE DOI 2310

WWW Link. Fast motion blur and low-light issues. BibRef

Peng, F.G.[Feng-Guang], Ding, Z.[Zihan], Chen, Z.M.[Zi-Ming], Wang, G.[Gang], Hui, T.R.[Tian-Rui], Liu, S.[Si], Shi, H.[Hang],
Region-adaptive and context-complementary cross modulation for RGB-T semantic segmentation,
PR(147), 2024, pp. 110092.
Elsevier DOI 2312
RGB-Thermal, Semantic segmentation, Region-Adaptive Channel Modulation, Context-Complementary Spatial Modulation BibRef

Zhou, W.[Wujie], Zhang, H.[Han], Yan, W.Q.[Wei-Qing], Lin, W.S.[Wei-Si],
MMSMCNet: Modal Memory Sharing and Morphological Complementary Networks for RGB-T Urban Scene Semantic Segmentation,
CirSysVideo(33), No. 12, December 2023, pp. 7096-7108.
IEEE DOI Code:
WWW Link. 2312
BibRef

Liang, Z.X.[Zhi-Xue], Dong, W.Y.[Wen-Yong], Zhang, B.[Bo],
TRACL: Temporal reconstruction and adaptive consistency loss for semi-supervised video semantic segmentation,
IET-IPR(18), No. 2, 2024, pp. 348-361.
DOI Link 2402
adaptive consistency loss, temporal reconstruction, video semantic segmentation BibRef

Li, X.T.[Xiang-Tai], Zhang, J.N.[Jiang-Ning], Yang, Y.[Yibo], Cheng, G.L.[Guang-Liang], Yang, K.Y.[Kui-Yuan], Tong, Y.H.[Yun-Hai], Tao, D.C.[Da-Cheng],
Sfnet: Faster and Accurate Semantic Segmentation Via Semantic Flow,
IJCV(132), No. 2, February 2024, pp. 466-489.
Springer DOI 2402
BibRef

An, S.[Shumin], Liao, Q.M.[Qing-Min], Lu, Z.Q.[Zong-Qing], Xue, J.H.[Jing-Hao],
Dual Correlation Network for Efficient Video Semantic Segmentation,
CirSysVideo(34), No. 3, March 2024, pp. 1572-1585.
IEEE DOI Code:
WWW Link. 2403
Semantic segmentation, Semantics, Correlation, Feature extraction, Redundancy, Schedules, Predictive models, key frame selection BibRef


Chen, X.C.[Xue-Chao], Xu, S.J.[Shuang-Jie], Zou, X.Y.[Xiao-Yi], Cao, T.Y.[Tong-Yi], Yeung, D.Y.[Dit-Yan], Fang, L.[Lu],
SVQNet: Sparse Voxel-Adjacent Query Network for 4D Spatio-Temporal LiDAR Semantic Segmentation,
ICCV23(8535-8544)
IEEE DOI 2401
BibRef

Aakanksha, Rajagopalan, A.N.,
Improving Robustness of Semantic Segmentation to Motion-Blur Using Class-Centric Augmentation,
CVPR23(10470-10479)
IEEE DOI 2309
BibRef

Su, J.M.[Jin-Ming], Yin, R.[Ruihong], Zhang, S.[Shuaibin], Luo, J.F.[Jun-Feng],
Motion-state Alignment for Video Semantic Segmentation,
PVUW23(3571-3580)
IEEE DOI 2309
BibRef

Ji, W.[Wei], Li, J.J.[Jing-Jing], Bian, C.[Cheng], Zhou, Z.[Zongwei], Zhao, J.Y.[Jia-Ying], Yuille, A.[Alan], Cheng, L.[Li],
Multispectral Video Semantic Segmentation: A Benchmark Dataset and Baseline,
CVPR23(1094-1104)
IEEE DOI 2309
BibRef

Cho, K.[Kyusik], Lee, S.[Suhyeon], Seong, H.[Hongje], Kim, E.T.[Eun-Tai],
Domain Adaptive Video Semantic Segmentation via Cross-Domain Moving Object Mixing,
WACV23(489-498)
IEEE DOI 2302
Training, Adaptation models, Filtering, Semantic segmentation, Benchmark testing, visual reasoning BibRef

Sun, G.[Guolei], Liu, Y.[Yun], Tang, H.[Hao], Chhatkuli, A.[Ajad], Zhang, L.[Le], Van Gool, L.J.[Luc J.],
Mining Relations Among Cross-Frame Affinities for Video Semantic Segmentation,
ECCV22(XXXIV:522-539).
Springer DOI 2211
BibRef

Wu, X.Y.[Xin-Yi], Wu, Z.Y.[Zhen-Yao], Wan, J.[Jin], Ju, L.[Lili], Wang, S.[Song],
Is It Necessary to Transfer Temporal Knowledge for Domain Adaptive Video Semantic Segmentation?,
ECCV22(XXVII:357-373).
Springer DOI 2211
BibRef

Zhao, W.[Wangbo], Wang, K.[Kai], Chu, X.X.[Xiang-Xiang], Xue, F.Z.[Fu-Zhao], Wang, X.C.[Xin-Chao], You, Y.[Yang],
Modeling Motion with Multi-Modal Features for Text-Based Video Segmentation,
CVPR22(11727-11736)
IEEE DOI 2210
Optical losses, Fuses, Motion segmentation, Design methodology, Semantics, Linguistics, Segmentation, grouping and shape analysis, Vision+language BibRef

Wei, D.L.[Dong-Lai], Kharbanda, S.[Siddhant], Arora, S.[Sarthak], Roy, R.[Roshan], Jain, N.[Nishant], Palrecha, A.[Akash], Shah, T.[Tanav], Mathur, S.[Shray], Mathur, R.[Ritik], Kemkar, A.[Abhijay], Chakravarthy, A.[Anirudh], Lin, Z.[Zudi], Jang, W.D.[Won-Dong], Tang, Y.S.[Yan-Song], Bai, S.[Song], Tompkin, J.[James], Torr, P.H.S.[Philip H.S.], Pfister, H.[Hanspeter],
YouMVOS: An Actor-centric Multi-shot Video Object Segmentation Dataset,
CVPR22(21012-21021)
IEEE DOI 2210
Video on demand, Tracking, Shape, Error analysis, Memory management, Memory architecture, Datasets and evaluation, Segmentation, grouping and shape analysis BibRef

Zhang, C.B.[Chang-Bin], Xiao, J.W.[Jia-Wen], Liu, X.[Xialei], Chen, Y.C.[Ying-Cong], Cheng, M.M.[Ming-Ming],
Representation Compensation Networks for Continual Semantic Segmentation,
CVPR22(7043-7054)
IEEE DOI 2210
Representation learning, Deep learning, Codes, Computational modeling, Semantics, Neural networks, grouping and shape analysis BibRef

Sun, G.[Guolei], Liu, Y.[Yun], Ding, H.H.[Heng-Hui], Probst, T.[Thomas], Van Gool, L.J.[Luc J.],
Coarse-to-Fine Feature Mining for Video Semantic Segmentation,
CVPR22(3116-3127)
IEEE DOI 2210
Image segmentation, Shape, Motion segmentation, Semantics, Benchmark testing, Data mining, Video analysis and understanding, grouping and shape analysis BibRef

Zhuang, J.[Jiafan], Wang, Z.[Zilei], Gao, Y.[Yuan],
Semi-Supervised Video Semantic Segmentation with Inter-Frame Feature Reconstruction,
CVPR22(3253-3261)
IEEE DOI 2210
Training, Image segmentation, Codes, Semantics, Supervised learning, Data models, Video analysis and understanding, Segmentation, grouping and shape analysis BibRef

Park, H.[Hyojin], Yessenbayev, A.[Alan], Singhal, T.[Tushar], Adhikari, N.K.[Navin Kumar], Zhang, Y.Z.[Yi-Zhe], Borse, S.M.[Shubhankar Mangesh], Cai, H.[Hong], Mayer, F.[Frank], Calidas, B.[Balaji], Pandey, N.P.[Nilesh Prasad], Yin, F.[Fei], Porikli, F.M.[Fatih M.],
Real-Time, Accurate, and Consistent Video Semantic Segmentation via Unsupervised Adaptation and Cross-Unit Deployment on Mobile Device,
CVPR22(21399-21406)
IEEE DOI 2210
Performance evaluation, Image segmentation, Technological innovation, Adaptation models, Semantics, Streaming media BibRef

Mao, Y.Y.[Yun-Yao], Wang, N.[Ning], Zhou, W.G.[Wen-Gang], Li, H.Q.[Hou-Qiang],
Joint Inductive and Transductive Learning for Video Object Segmentation,
ICCV21(9650-9659)
IEEE DOI 2203
Video sequences, Training data, Object segmentation, Benchmark testing, Transformers, BibRef

Liang, S.X.[Shu-Xian], Shen, X.[Xu], Huang, J.Q.[Jian-Qiang], Hua, X.S.[Xian-Sheng],
Video Object Segmentation with Dynamic Memory Networks and Adaptive Object Alignment,
ICCV21(8045-8054)
IEEE DOI 2203
Visualization, Adaptation models, Adaptive systems, Codes, Annotations, Dynamics, Video analysis and understanding, grouping and shape BibRef

Wang, H.[Hao], Wang, W.[Weining], Liu, J.[Jing],
Temporal Memory Attention for Video Semantic Segmentation,
ICIP21(2254-2258)
IEEE DOI 2201
Image segmentation, Computational modeling, Semantics, Video sequences, Computational efficiency, self-attention BibRef

Kuhn, C.B.[Christopher B.], Hofbauer, M.[Markus], Xu, Z.Q.[Zi-Qin], Petrovic, G.[Goran], Steinbach, E.[Eckehard],
Pixel-Wise Failure Prediction for Semantic Video Segmentation,
ICIP21(614-618)
IEEE DOI 2201
Training, Image segmentation, Semantics, Noise reduction, Video sequences, Refining, Predictive models, Recurrent Neural Network BibRef

Jeon, S.[Sangryul], Min, D.B.[Dong-Bo], Kim, S.[Seungryong], Sohn, K.H.[Kwang-Hoon],
Mining Better Samples for Contrastive Learning of Temporal Correspondence,
CVPR21(1034-1044)
IEEE DOI 2111
Training, Uncertainty, Annotations, Pipelines, Measurement uncertainty, Pattern recognition BibRef

Nirkin, Y.[Yuval], Wolf, L.B.[Lior B.], Hassner, T.[Tal],
HyperSeg: Patch-wise Hypernetwork for Real-time Semantic Segmentation,
CVPR21(4060-4069)
IEEE DOI 2111
Image segmentation, Head, Runtime, Semantics, Memory management, Benchmark testing, Real-time systems BibRef

Zheng, S.X.[Si-Xiao], Lu, J.C.[Jia-Chen], Zhao, H.S.[Heng-Shuang], Zhu, X.T.[Xia-Tian], Luo, Z.[Zekun], Wang, Y.B.[Ya-Biao], Fu, Y.W.[Yan-Wei], Feng, J.F.[Jian-Feng], Xiang, T.[Tao], Torr, P.H.S.[Philip H.S.], Zhang, L.[Li],
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers,
CVPR21(6877-6886)
IEEE DOI 2111
Image segmentation, Visualization, Semantics, Transformers, Decoding, Pattern recognition, Servers BibRef

Fan, M.Y.[Ming-Yuan], Lai, S.[Shenqi], Huang, J.[Junshi], Wei, X.M.[Xiao-Ming], Chai, Z.H.[Zhen-Hua], Luo, J.F.[Jun-Feng], Wei, X.L.[Xiao-Lin],
Rethinking BiSeNet For Real-time Semantic Segmentation,
CVPR21(9711-9720)
IEEE DOI 2111
Image segmentation, Visualization, Semantics, Redundancy, Object detection, Feature extraction, Real-time systems BibRef

Varghese, S.[Serin], Gujamagadi, S.[Sharat], Klingner, M.[Marvin], Kapoor, N.[Nikhil], Bär, A.[Andreas], Schneider, J.D.[Jan David], Maag, K.[Kira], Schlicht, P.[Peter], Hüger, F.[Fabian], Fingscheidt, T.[Tim],
An Unsupervised Temporal Consistency (TC) Loss to Improve the Performance of Semantic Segmentation Networks,
SAIAD21(12-20)
IEEE DOI 2109
Training, Deep learning, Measurement, Image segmentation, Semantics, Video sequences, Neural networks BibRef

Lu, H.C.[Hong-Chao], Deng, Z.D.[Zhi-Dong],
A Boundary-aware Distillation Network for Compressed Video Semantic Segmentation,
ICPR21(5354-5359)
IEEE DOI 2105
Knowledge engineering, Motion segmentation, Semantics, Streaming media, Pattern recognition, Acceleration, Task analysis BibRef

Sellami, A.[Akrem], Tabbone, S.[Salvatore],
Video semantic segmentation using deep multi-view representation learning,
ICPR21(1-7)
IEEE DOI 2105
Deep learning, Correlation, Motion segmentation, Semantics, Training data, Object segmentation, Feature extraction, fully convolutional network BibRef

Chen, Y.H.[Yi-Hong], Cao, Y.[Yue], Hu, H.[Han], Wang, L.W.[Li-Wei],
Memory Enhanced Global-Local Aggregation for Video Object Detection,
CVPR20(10334-10343)
IEEE DOI 2008
Semantics, Object detection, Feature extraction, Detectors, Aggregates, Object recognition, Optical imaging BibRef

Huang, X.H.[Xu-Hua], Xu, J.R.[Jia-Rui], Tai, Y.W.[Yu-Wing], Tang, C.K.[Chi-Keung],
Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template Matching,
CVPR20(8876-8886)
IEEE DOI 2008
Object segmentation, Pipelines, Benchmark testing, Semantics, Image segmentation, Task analysis, Feature extraction BibRef

Lu, X., Wang, W., Shen, J., Tai, Y., Crandall, D.J., Hoi, S.C.H.,
Learning Video Object Segmentation From Unlabeled Videos,
CVPR20(8957-8967)
IEEE DOI 2008
Semantics, Supervised learning, Visualization, Training, Data models, Object segmentation, Machine learning BibRef

Hu, P., Caba, F., Wang, O., Lin, Z., Sclaroff, S., Perazzi, F.,
Temporally Distributed Networks for Fast Video Semantic Segmentation,
CVPR20(8815-8824)
IEEE DOI 2008
Feature extraction, Computational modeling, Image segmentation, Semantics, Aggregates, Encoding, Task analysis BibRef

Bujanca, M., Lujan, M., Lennox, B.,
FullFusion: A Framework for Semantic Reconstruction of Dynamic Scenes,
3D-Wild19(2168-2177)
IEEE DOI 2004
image colour analysis, image motion analysis, image reconstruction, image segmentation, mobile robots, dynamic SLAM BibRef

Li, Y., Shi, J., Lin, D.,
Low-Latency Video Semantic Segmentation,
CVPR18(5997-6005)
IEEE DOI 1812
Semantics, Image segmentation, Convolution, Kernel, Task analysis, Feeds, Streaming media BibRef

Xu, Y., Fu, T., Yang, H., Lee, C.,
Dynamic Video Segmentation Network,
CVPR18(6556-6565)
IEEE DOI 1812
Semantics, Image segmentation, Feature extraction, Video sequences, Acceleration, Adaptive scheduling BibRef

Nilsson, D., Sminchisescu, C.,
Semantic Video Segmentation by Gated Recurrent Flow Propagation,
CVPR18(6819-6828)
IEEE DOI 1812
Semantics, Logic gates, Optical network units, Image segmentation, Adaptation models, Motion segmentation BibRef

Jain, S.[Samvit], Gonzalez, J.E.[Joseph E.],
Fast Semantic Segmentation on Video Using Block Motion-Based Feature Interpolation,
VSeg18(IV:3-6).
Springer DOI 1905
BibRef

Zhu, Y.[Yi], Sapra, K.[Karan], Reda, F.A.[Fitsum A.], Shih, K.J.[Kevin J.], Newsam, S.[Shawn], Tao, A.[Andrew], Catanzaro, B.[Bryan],
Improving Semantic Segmentation via Video Propagation and Label Relaxation,
CVPR19(8848-8857).
IEEE DOI 2002
BibRef

Chandra, S., Couprie, C., Kokkinos, I.[Iasonas],
Deep Spatio-Temporal Random Fields for Efficient Video Segmentation,
CVPR18(8915-8924)
IEEE DOI 1812
Image segmentation, Semantics, Task analysis, Linear systems, Inference algorithms, Prediction algorithms BibRef

Huang, P.Y.[Po-Yu], Hsu, W.T.[Wan-Ting], Chiu, C.Y.[Chun-Yueh], Wu, T.F.[Ting-Fan], Sun, M.[Min],
Efficient Uncertainty Estimation for Semantic Segmentation in Videos,
ECCV18(I: 536-552).
Springer DOI 1810
BibRef

Hong, S., Yeo, D., Kwak, S., Lee, H., Han, B.,
Weakly Supervised Semantic Segmentation Using Web-Crawled Videos,
CVPR17(2224-2232)
IEEE DOI 1711
Decoding, Image segmentation, Motion segmentation, Optimization, Semantics, Videos BibRef

Mahasseni, B., Todorovic, S., Fern, A.,
Budget-Aware Deep Semantic Video Segmentation,
CVPR17(2077-2086)
IEEE DOI 1711
Feature extraction, Interpolation, Labeling, Runtime, Semantics, Training BibRef

He, Y.[Yang], Chiu, W.C., Keuper, M.[Margret], Fritz, M.[Mario],
STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling,
CVPR17(7158-7167)
IEEE DOI 1711
Image segmentation, Indexes, Optical imaging, Semantics, Training, Videos BibRef

Kundu, A.[Abhijit], Vineet, V.[Vibhav], Koltun, V.[Vladlen],
Feature Space Optimization for Semantic Video Segmentation,
CVPR16(3168-3175)
IEEE DOI 1612
BibRef

Wang, H.L.[Hui-Ling], Raiko, T.[Tapani], Lensu, L.[Lasse], Wang, T.H.[Ting-Huai], Karhunen, J.[Juha],
Semi-supervised Domain Adaptation for Weakly Labeled Semantic Video Object Segmentation,
ACCV16(I: 163-179).
Springer DOI 1704
BibRef

Mustikovela, S.K.[Siva Karthik], Yang, M.Y.[Michael Ying], Rother, C.[Carsten],
Can Ground Truth Label Propagation from Video Help Semantic Segmentation?,
VSeg16(III: 804-820).
Springer DOI 1611
BibRef

Zheng, S.[Shuai], Cheng, M.M.[Ming-Ming], Warrell, J.[Jonathan], Sturgess, P.[Paul], Vineet, V.[Vibhav], Rother, C.[Carsten], Torr, P.H.S.[Philip H.S.],
Dense Semantic Image Segmentation with Objects and Attributes,
CVPR14(3214-3221)
IEEE DOI 1409
Attributes, Image Segmentation, Object Recognition, Scene Understanding BibRef

Jain, A.[Aastha], Chatterjee, S.[Shuanak], Vidal, R.[Rene],
Coarse-to-Fine Semantic Video Segmentation Using Supervoxel Trees,
ICCV13(1865-1872)
IEEE DOI 1403
Image segmentation BibRef

Dunlop, H.[Heather],
Scene classification of images and video via semantic segmentation,
POCV10(72-79).
IEEE DOI 1006
BibRef

Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Motion Segmentation, Neural Networks, Learning .


Last update:Mar 16, 2024 at 20:36:19