18.3.4.1 Motion Segmentation, Neural Networks, Learning

Chapter Contents (Back)
Motion Segmentation. Neural Networks. Learning.

Li, X.D.[Xu-Dong], Ye, M.[Mao], Liu, Y.G.[Yi-Guang], Zhang, F.[Feng], Liu, D.[Dan], Tang, S.[Song],
Accurate object detection using memory-based models in surveillance scenes,
PR(67), No. 1, 2017, pp. 73-84.
Elsevier DOI 1704
Convolutional neural network BibRef

Cheng, K.W.[Kai-Wen], Chen, Y.T.[Yie-Tarng], Fang, W.H.[Wen-Hsien],
Improved Object Detection With Iterative Localization Refinement in Convolutional Neural Networks,
CirSysVideo(28), No. 9, September 2018, pp. 2261-2275.
IEEE DOI 1809
BibRef
Earlier:
Iterative localization refinement in convolutional neural networks for improved object detection,
ICIP16(3643-3647)
IEEE DOI 1610
Proposals, Object detection, Feature extraction, Detectors, Neural networks, Search problems, Iterative methods, localization refinement. Iterative methods BibRef

Yin, H.[Hui], Yang, L.[Lin], Xu, H.L.[Hong-Li], Wan, J.[Jin],
Adaptive convolutional neural network for large change in video object segmentation,
IET-CV(13), No. 5, August 2019, pp. 452-460.
DOI Link 1908
BibRef

Chen, Y.Y.[Ying-Ying], Wang, J.Q.[Jin-Qiao], Zhu, B.[Bingke], Tang, M.[Ming], Lu, H.Q.[Han-Qing],
Pixelwise Deep Sequence Learning for Moving Object Detection,
CirSysVideo(29), No. 9, September 2019, pp. 2567-2579.
IEEE DOI 1909
Semantics, Feature extraction, Object detection, Cameras, Image color analysis, Lighting, Moving object detection, convolutional neural networks BibRef


Paul, M., Mayer, C., Van Gool, L.J., Timofte, R.,
Efficient Video Semantic Segmentation with Labels Propagation and Refinement,
WACV20(2862-2871)
IEEE DOI 2006
Semantics, Image segmentation, Optical imaging, Pipelines, Integrated optics, Graphics processing units, Streaming media, Refinement BibRef

Hu, P., Liu, J., Wang, G., Ablavsky, V., Saenko, K., Sclaroff, S.,
DIPNet: Dynamic Identity Propagation Network for Video Object Segmentation,
WACV20(1893-1902)
IEEE DOI 2006
Robustness, Semantics, Image segmentation, Encoding, Task analysis, Adaptation models, Feature extraction BibRef

Xu, K.[Kai], Wen, L.Y.[Long-Yin], Li, G.R.[Guo-Rong], Bo, L.F.[Lie-Feng], Huang, Q.M.[Qing-Ming],
Spatiotemporal CNN for Video Object Segmentation,
CVPR19(1379-1388).
IEEE DOI 2002
BibRef

Wang, S., Group, A., Lu, H., Deng, Z.,
Fast Object Detection in Compressed Video,
ICCV19(7103-7112)
IEEE DOI 2004
convolutional neural nets, data compression, feature extraction, image motion analysis, learning (artificial intelligence), Machine learning BibRef

Lao, D., Sundaramoorthi, G.,
Minimum Delay Object Detection From Video,
ICCV19(5096-5105)
IEEE DOI 2004
BibRef
Earlier:
Minimum Delay Moving Object Detection,
CVPR17(4809-4818)
IEEE DOI 1711
convolutional neural nets, object detection, video signal processing, online fashion, real-time solution, Object detection. Cameras, Delays, Estimation, Motion segmentation, Reliability BibRef

Zeng, X., Liao, R., Gu, L., Xiong, Y., Fidler, S., Urtasun, R.,
DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation,
ICCV19(3928-3937)
IEEE DOI 2004
convolutional neural nets, gradient methods, image matching, image segmentation, learning (artificial intelligence), Task analysis BibRef

Lyu, Y., Vosselman, G., Xia, G., Yang, M.Y.,
LIP: Learning Instance Propagation for Video Object Segmentation,
MCMV19(2739-2748)
IEEE DOI 2004
convolutional neural nets, image segmentation, learning (artificial intelligence), object detection, memory module BibRef

Wang, Z., Xu, J., Liu, L., Zhu, F., Shao, L.,
RANet: Ranking Attention Network for Fast Video Object Segmentation,
ICCV19(3977-3986)
IEEE DOI 2004
Code, Video Object Segmentatioin.
WWW Link. image matching, image segmentation, neural nets, object detection, supervised learning, video signal processing, Real-time systems BibRef

Zhang, L., Lin, Z., Zhang, J., Lu, H., He, Y.,
Fast Video Object Segmentation via Dynamic Targeting Network,
ICCV19(5581-5590)
IEEE DOI 2004
convolutional neural nets, image motion analysis, image segmentation, video signal processing, Strain BibRef

Sibechi, R., Booij, O., Baka, N., Bloem, P.,
Exploiting Temporality for Semi-Supervised Video Segmentation,
CVRSUAD19(933-941)
IEEE DOI 2004
convolutional neural nets, image annotation, image classification, image segmentation, supervised learning, Semi Supervised BibRef

Wang, W., Lu, X., Shen, J., Crandall, D., Shao, L.,
Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks,
ICCV19(9235-9244)
IEEE DOI 2004
graph theory, image segmentation, image sequences, learning (artificial intelligence), message passing, neural nets, Image segmentation BibRef

Wu, H., Chen, Y., Wang, N., Zhang, Z.,
Sequence Level Semantics Aggregation for Video Object Detection,
ICCV19(9216-9224)
IEEE DOI 2004
feature extraction, image sequences, neural nets, object detection, pattern clustering, video signal processing, VID problem, Adaptive optics BibRef

Sultana, M., Mahmood, A., Bouwmans, T., Jung, S.K.,
Complete Moving Object Detection in the Context of Robust Subspace Learning,
RSL-CV19(661-668)
IEEE DOI 2004
computer vision, image motion analysis, image segmentation, learning (artificial intelligence), neural nets, Robust Subspace Learning BibRef

Zhou, Q., Huang, Z., Huang, L., Gong, Y., Shen, H., Liu, W., Wang, X.,
Motion-Guided Spatial Time Attention for Video Object Segmentation,
YouTube-VOS19(693-696)
IEEE DOI 2004
image motion analysis, image recognition, image segmentation, image sequences, learning (artificial intelligence), neural nets, object BibRef

Zhou, Z., Ren, L., Xiong, P., Ji, Y., Wang, P., Fan, H., Liu, S.,
Enhanced Memory Network for Video Segmentation,
YouTube-VOS19(689-692)
IEEE DOI 2004
feature extraction, image segmentation, neural nets, supervised learning, video signal processing, ASPP module, memory network BibRef

Feng, Q., Yang, Z., Li, P., Wei, Y., Yang, Y.,
Dual Embedding Learning for Video Instance Segmentation,
YouTube-VOS19(717-720)
IEEE DOI 2004
embedded systems, image segmentation, learning (artificial intelligence), neural nets, instance embedding learning BibRef

Dong, M., Wang, J., Huang, Y., Yu, D., Su, K., Zhou, K., Shao, J., Wen, S., Wang, C.,
Temporal Feature Augmented Network for Video Instance Segmentation,
YouTube-VOS19(721-724)
IEEE DOI 2004
convolutional neural nets, feature extraction, image motion analysis, image segmentation, object detection, Deep Learning BibRef

Liu, X., Ren, H., Ye, T.,
Spatio-Temporal Attention Network for Video Instance Segmentation,
YouTube-VOS19(725-727)
IEEE DOI 2004
convolutional neural nets, image segmentation, object detection, video signal processing, Youtube VIS test dataset, spatio temporal BibRef

Luiten, J.[Jonathon], Torr, P.H.S.[Philip H.S.], Leibe, B.[Bastian],
Video Instance Segmentation 2019: A Winning Approach for Combined Detection, Segmentation, Classification and Tracking.,
YouTube-VOS19(709-712)
IEEE DOI 2004
image classification, image segmentation, learning (artificial intelligence), neural nets, object tracking, Classification BibRef

Yu, D., Su, K., Guo, H., Wang, J., Zhou, K., Huang, Y., Dong, M., Shao, J., Wang, C.,
Towards Good Practices for Video Object Segmentation,
YouTube-VOS19(701-704)
IEEE DOI 2004
image segmentation, learning (artificial intelligence), social networking (online), video signal processing, Convolutional Neural Network BibRef

Liu, D., Yu, R., Su, H.,
Extending Adversarial Attacks and Defenses to Deep 3D Point Cloud Classifiers,
ICIP19(2279-2283)
IEEE DOI 1910
adversarial attack, adversarial defense, 3D point cloud, deep neural network, fast gradient method BibRef

Zhu, M., Liu, M.,
Mobile Video Object Detection with Temporally-Aware Feature Maps,
CVPR18(5686-5695)
IEEE DOI 1812
Feature extraction, Computational modeling, Object detection, Detectors, Computer architecture, Streaming media, Neural networks BibRef

Yang, L., Wang, Y., Xiong, X., Yang, J., Katsaggelos, A.K.,
Efficient Video Object Segmentation via Network Modulation,
CVPR18(6499-6507)
IEEE DOI 1812
Modulation, Visualization, Adaptation models, Image segmentation, Task analysis, Motion segmentation, Neural networks BibRef

Bideau, P.[Pia], Roy Chowdhury, A., Menon, R.R.[Rakesh R.], Learned-Miller, E.G.[Erik G.],
The Best of Both Worlds: Combining CNNs and Geometric Constraints for Hierarchical Motion Segmentation,
CVPR18(508-517)
IEEE DOI 1812
Motion segmentation, Computer vision, Optical imaging, Cameras, Semantics, Animals BibRef

Li, S., Seybold, B., Vorobyov, A., Fathi, A., Huang, Q., Kuo, C.C.J.,
Instance Embedding Transfer to Unsupervised Video Object Segmentation,
CVPR18(6526-6535)
IEEE DOI 1812
Image segmentation, Object segmentation, Motion segmentation, Optical imaging, Semantics, Task analysis, Neural networks BibRef

Yurdakul, E.E., Yemez, Y.,
Semantic Segmentation of RGBD Videos with Recurrent Fully Convolutional Neural Networks,
MSF17(367-374)
IEEE DOI 1802
Computer architecture, Image color analysis, Image segmentation, Neural networks, Semantics, Videos BibRef

Teney, D.[Damien], Hebert, M.[Martial],
Learning to Extract Motion from Videos in Convolutional Neural Networks,
ACCV16(V: 412-428).
Springer DOI 1704
BibRef

Teney, D.[Damien], Brown, M.[Matthew], Kit, D.[Dimitry], Hall, P.[Peter],
Learning similarity metrics for dynamic scene segmentation,
CVPR15(2084-2093)
IEEE DOI 1510
BibRef

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


Last update:Jul 10, 2020 at 16:03:35