Yeo, C.,
Ahammad, P.,
Ramchandran, K.,
Sastry, S.S.,
High-Speed Action Recognition and Localization in Compressed Domain
Videos,
CirSysVideo(18), No. 8, August 2008, pp. 1006-1015.
IEEE DOI
0809
BibRef
Cho, J.C.[Jung-Chan],
Lee, M.[Minsik],
Chang, H.J.[Hyung Jin],
Oh, S.H.[Song-Hwai],
Robust action recognition using local motion and group sparsity,
PR(47), No. 5, 2014, pp. 1813-1825.
Elsevier DOI
1402
Action recognition
BibRef
Wang, G.F.[Guo-Feng],
Qin, X.Y.[Xue-Ying],
Zhong, F.[Fan],
Liu, Y.[Yue],
Li, H.B.[Hong-Bo],
Peng, Q.S.[Qun-Sheng],
Yang, M.H.[Ming-Hsuan],
Visual Tracking via Sparse and Local Linear Coding,
IP(24), No. 11, November 2015, pp. 3796-3809.
IEEE DOI
1509
image coding
BibRef
Earlier: A1, A3, A4, A6, A2, Only:
Visual Tracking in Continuous Appearance Space via Sparse Coding,
ACCV12(III:57-70).
Springer DOI
1304
See also Visual Tracking via Temporally Smooth Sparse Coding.
See also Visual Tracking via Coarse and Fine Structural Local Sparse Appearance Models.
BibRef
Qi, Y.K.[Yuan-Kai],
Qin, L.[Lei],
Zhang, J.[Jian],
Zhang, S.P.[Sheng-Ping],
Huang, Q.M.[Qing-Ming],
Yang, M.H.[Ming-Hsuan],
Structure-Aware Local Sparse Coding for Visual Tracking,
IP(27), No. 8, August 2018, pp. 3857-3869.
IEEE DOI
1806
image coding, image representation, image sequences,
object tracking, target tracking, dictionary,
template update
BibRef
Jain, M.[Mihir],
van Gemert, J.[Jan],
Jégou, H.[Hervé],
Bouthemy, P.[Patrick],
Snoek, C.G.M.[Cees G. M.],
Tubelets: Unsupervised Action Proposals from Spatiotemporal
Super-Voxels,
IJCV(124), No. 3, September 2017, pp. 287-311.
Springer DOI
1708
BibRef
Earlier:
Action Localization with Tubelets from Motion,
CVPR14(740-747)
IEEE DOI
1409
determine when and where certain actions appear.
BibRef
Jain, M.[Mihir],
van Gemert, J.C.[Jan C.],
Snoek, C.G.M.[Cees G.M.],
What do 15,000 object categories tell us about classifying and
localizing actions?,
CVPR15(46-55)
IEEE DOI
1510
BibRef
Mettes, P.S.[Pascal S.],
Snoek, C.G.M.[Cees G. M.],
Spatial-Aware Object Embeddings for Zero-Shot Localization and
Classification of Actions,
ICCV17(4453-4462)
IEEE DOI
1802
image classification, image motion analysis, object detection,
object recognition, video signal processing,
Trajectory
BibRef
Mettes, P.S.[Pascal S.],
Snoek, C.G.M.[Cees G. M.],
Pointly-Supervised Action Localization,
IJCV(127), No. 3, March 2019, pp. 263-281.
Springer DOI
1903
Localization by finding bounding boxes.
BibRef
Mettes, P.S.[Pascal S.],
van Gemert, J.C.[Jan C.],
Snoek, C.G.M.[Cees G. M.],
Spot On: Action Localization from Pointly-Supervised Proposals,
ECCV16(V: 437-453).
Springer DOI
1611
BibRef
van Gemert, J.C.[Jan C.],
Jain, M.[Mihir],
Gati, E.[Ella],
Snoek, C.G.M.[Cees G.M.],
APT: Action localization proposals from dense trajectories,
BMVC15(xx-yy).
DOI Link
1601
BibRef
Jain, M.[Mihir],
van Gemert, J.C.[Jan C.],
Mensink, T.[Thomas],
Snoek, C.G.M.[Cees G.M.],
Objects2action:
Classifying and Localizing Actions without Any Video Example,
ICCV15(4588-4596)
IEEE DOI
1602
Computational modeling
BibRef
Soomro, K.[Khurram],
Idrees, H.[Haroon],
Shah, M.[Mubarak],
Online Localization and Prediction of Actions and Interactions,
PAMI(41), No. 2, February 2019, pp. 459-472.
IEEE DOI
1901
BibRef
Earlier:
Predicting the Where and What of Actors and Actions through Online
Action Localization,
CVPR16(2648-2657)
IEEE DOI
1612
BibRef
Earlier:
Action Localization in Videos through Context Walk,
ICCV15(3280-3288)
IEEE DOI
1602
Videos, Support vector machines, Predictive models,
Motion segmentation, Visualization, Training, Dynamic programming,
structural SVM.
Context
BibRef
Soomro, K.[Khurram],
Shah, M.[Mubarak],
Unsupervised Action Discovery and Localization in Videos,
ICCV17(696-705)
IEEE DOI
1802
directed graphs, feature extraction, image classification,
image segmentation, knapsack problems, pattern clustering,
Videos
BibRef
Song, H.,
Wu, X.,
Zhu, B.,
Wu, Y.,
Chen, M.,
Jia, Y.,
Temporal Action Localization in Untrimmed Videos Using Action Pattern
Trees,
MultMed(21), No. 3, March 2019, pp. 717-730.
IEEE DOI
1903
data mining, feature extraction, image motion analysis,
image segmentation, learning (artificial intelligence),
overlap loss function
BibRef
Zeng, R.H.[Run-Hao],
Gan, C.[Chuang],
Chen, P.H.[Pei-Hao],
Huang, W.B.[Wen-Bing],
Wu, Q.Y.[Qing-Yao],
Tan, M.K.[Ming-Kui],
Breaking Winner-Takes-All: Iterative-Winners-Out Networks for Weakly
Supervised Temporal Action Localization,
IP(28), No. 12, December 2019, pp. 5797-5808.
IEEE DOI
1909
Videos, Training, Proposals, Image segmentation, Correlation,
Object detection, Semantics, Weakly supervised learning,
untrimmed video
BibRef
Zhang, Y.Q.[Yong-Qiang],
Ding, M.L.[Ming-Li],
Bai, Y.C.[Yan-Cheng],
Liu, D.[Dandan],
Ghanem, B.[Bernard],
Learning a strong detector for action localization in videos,
PRL(128), 2019, pp. 407-413.
Elsevier DOI
1912
Frame-level object detection, Deformable anchor cuboid, Action localization
BibRef
Heilbron, F.C.[Fabian Caba],
Lee, J.Y.[Joon-Young],
Jin, H.L.[Hai-Lin],
Ghanem, B.[Bernard],
What Do I Annotate Next? An Empirical Study of Active Learning for
Action Localization,
ECCV18(XI: 212-229).
Springer DOI
1810
BibRef
Heilbron, F.C.[Fabian Caba],
Barrios, W.,
Escorcia, V.,
Ghanem, B.[Bernard],
SCC: Semantic Context Cascade for Efficient Action Detection,
CVPR17(3175-3184)
IEEE DOI
1711
Computational modeling, Context modeling, Dogs, Legged locomotion,
Proposals, Semantics, Video, sequences
BibRef
Escorcia, V.[Victor],
Heilbron, F.C.[Fabian Caba],
Niebles, J.C.[Juan Carlos],
Ghanem, B.[Bernard],
DAPs: Deep Action Proposals for Action Understanding,
ECCV16(III: 768-784).
Springer DOI
1611
BibRef
Heilbron, F.C.[Fabian Caba],
Thabet, A.[Ali],
Niebles, J.C.[Juan Carlos],
Ghanem, B.[Bernard],
Camera Motion and Surrounding Scene Appearance as Context for Action
Recognition,
ACCV14(IV: 583-597).
Springer DOI
1504
BibRef
Liu, D.C.[Dao-Chang],
Jiang, T.T.[Ting-Ting],
Wang, Y.[Yizhou],
Completeness Modeling and Context Separation for Weakly Supervised
Temporal Action Localization,
CVPR19(1298-1307).
IEEE DOI
2002
BibRef
Su, R.[Rui],
Ouyang, W.L.[Wan-Li],
Zhou, L.P.[Lu-Ping],
Xu, D.[Dong],
Improving Action Localization by Progressive Cross-Stream Cooperation,
CVPR19(12008-12017).
IEEE DOI
2002
BibRef
Wang, W.N.[Wei-Ning],
Huang, Y.[Yan],
Wang, L.[Liang],
Language-Driven Temporal Activity Localization:
A Semantic Matching Reinforcement Learning Model,
CVPR19(334-343).
IEEE DOI
2002
BibRef
Long, F.C.[Fu-Chen],
Yao, T.[Ting],
Qiu, Z.F.[Zhao-Fan],
Tian, X.M.[Xin-Mei],
Luo, J.B.[Jie-Bo],
Mei, T.[Tao],
Gaussian Temporal Awareness Networks for Action Localization,
CVPR19(344-353).
IEEE DOI
2002
BibRef
Li, H.,
Yang, J.,
Zhou, Y.,
Li, S.,
Rethinking Temporal Structure Modeling Method for Temporal Action
Localization,
ICIP19(3676-3680)
IEEE DOI
1910
Action localization, spatial-temporal feature,
video content analysis, supervised learning
BibRef
Nguyen, P.,
Han, B.,
Liu, T.,
Prasad, G.,
Weakly Supervised Action Localization by Sparse Temporal Pooling
Network,
CVPR18(6752-6761)
IEEE DOI
1812
Videos, Proposals, Feature extraction, Task analysis,
Convolutional neural networks, Prediction algorithms
BibRef
Vial, R.,
Zhu, H.,
Tian, Y.,
Lu, S.,
Search video action proposal with recurrent and static YOLO,
ICIP17(2035-2039)
IEEE DOI
1803
Clutter, Detectors, Dynamic programming, Labeling, Object detection,
Proposals, Training, action detection, action localization,
video object proposal
BibRef
Shao, D.[Dian],
Xiong, Y.[Yu],
Zhao, Y.[Yue],
Huang, Q.Q.[Qing-Qiu],
Qiao, Y.[Yu],
Lin, D.[Dahua],
Find and Focus: Retrieve and Localize Video Events with Natural
Language Queries,
ECCV18(IX: 202-218).
Springer DOI
1810
BibRef
Sharir, G.[Gilad],
Tuytelaars, T.[Tinne],
Action in chains:
A chains model for action localization and classification,
WACV14(610-617)
IEEE DOI
1406
Computational modeling
BibRef
Ta, A.P.[Anh-Phuong],
Wolf, C.[Christian],
Lavoue, G.[Guillaume],
Baskurt, A.[Atilla],
Jolion, J.M.[Jean-Michel],
Pairwise Features for Human Action Recognition,
ICPR10(3224-3227).
IEEE DOI
1008
BibRef
And: A1, A2, A3, A4, Only:
Recognizing and Localizing Individual Activities through Graph Matching,
AVSS10(196-203).
IEEE DOI
1009
BibRef
Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Accumulation Methods, Motion Histograms for Human Action Recognition .