17.1.4.6 Action Recognition for Untrimmed Videos

Chapter Contents (Back)
Action Recognition. Action Detection. Action Segmentation. Untrimmed Video. 2608

See also Action Localization, Action Localisation.
See also Action Segmentation, Action Start.

Song, H.[Hao], Wu, X.X.[Xin-Xiao], Zhu, B.[Bing], Wu, Y.W.[Yu-Wei], Chen, M.[Mei], Jia, Y.D.[Yun-De],
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

Zhou, Z.L.[Zhi-Li], Ding, C.[Chun], Li, J.[Jin], Mohammadi, E.[Eman], Liu, G.C.[Guang-Can], Yang, Y.M.[Yi-Min], Wu, Q.M.J.[Q. M. Jonathan],
Sequential Order-Aware Coding-Based Robust Subspace Clustering for Human Action Recognition in Untrimmed Videos,
IP(32), 2023, pp. 13-28.
IEEE DOI 2301
Videos, Codes, Feature extraction, Motion segmentation, Clustering algorithms, Task analysis, Image coding, untrimmed video BibRef

Jiang, Y.G.[Yu-Gang], Li, Z., Chang, S.F.[Shih-Fu],
Modeling Scene and Object Contexts for Human Action Retrieval With Few Examples,
CirSysVideo(21), No. 5, May 2011, pp. 674-681.
IEEE DOI 1105
Context from the background scene. Based on 10 basic actions. BibRef

Liu, Y.[Yuan], Ma, L.[Lin], Zhang, Y.F.[Yi-Feng], Liu, W.[Wei], Chang, S.F.[Shih-Fu],
Multi-Granularity Generator for Temporal Action Proposal,
CVPR19(3599-3608).
IEEE DOI 2002
BibRef

Shou, Z.[Zheng], Gao, H.[Hang], Zhang, L.[Lei], Miyazawa, K.[Kazuyuki], Chang, S.F.[Shih-Fu],
AutoLoc: Weakly-Supervised Temporal Action Localization in Untrimmed Videos,
ECCV18(XVI: 162-179).
Springer DOI 1810
BibRef

Shou, Z.[Zheng], Wang, D.A.[Dong-Ang], Chang, S.F.[Shih-Fu],
Temporal Action Localization in Untrimmed Videos via Multi-stage CNNs,
CVPR16(1049-1058)
IEEE DOI 1612
BibRef

Shou, Z.[Zheng], Chan, J., Zareian, A., Miyazawa, K., Chang, S.F.[Shih-Fu],
CDC: Convolutional-De-Convolutional Networks for Precise Temporal Action Localization in Untrimmed Videos,
CVPR17(1417-1426)
IEEE DOI 1711
Convolution, Feature extraction, Kernel, Proposals, Semantics, Videos BibRef

Hu, X.J.[Xue-Jiao], Wang, S.J.[Shi-Jie], Li, M.[Ming], Li, Y.[Yang], Du, S.[Sidan],
Distribution-Aware Activity Boundary Representation for Online Detection of Action Start in Untrimmed Videos,
SPLetters(31), 2024, pp. 765-769.
IEEE DOI 2403
Location awareness, Videos, Training, Task analysis, Representation learning, Standards, Uncertainty, distribution-aware activity boundary BibRef

Yan, S.[Sheng], Liu, M.Y.[Meng-Yuan], Wang, Y.[Yong], Liu, Y.[Yang], Liu, H.[Hong],
MLP: Motion Label Prior for Temporal Sentence Localization in Untrimmed 3D Human Motions,
CirSysVideo(34), No. 11, November 2024, pp. 11535-11550.
IEEE DOI Code:
WWW Link. 2412
Location awareness, Training, Task analysis, Semantics, Temporal grounding, human motion, corpus moment retrieval BibRef

Tang, Y.[Yi], Chen, M.S.[Man-Sen], Chen, L.P.[Le-Peng], Wang, S.[Sen], Liu, M.[Min], Wang, Y.N.[Yao-Nan], Liu, J.[Jun],
Information-Bottleneck-Guided Hybrid Neural Architecture Search for Temporal Action Detection in Untrimmed Videos,
IP(35), 2026, pp. 8664-8677.
IEEE DOI Code:
WWW Link. 2608
Transformers, Architecture, Videos, Modeling, Neural architecture search, Signal detection, Location awareness, video understanding BibRef


Yang, M.[Min], Gao, H.[Huan], Guo, P.[Ping], Wang, L.M.[Li-Min],
Adapting Short-Term Transformers for Action Detection in Untrimmed Videos,
CVPR24(18570-18579)
IEEE DOI 2410
Adaptation models, Computational modeling, Memory management, Detectors, Transformers, Feature extraction, Vision Transformer BibRef

Geng, T.T.[Tian-Tian], Wang, T.[Teng], Duan, J.M.[Jin-Ming], Cong, R.M.[Run-Min], Zheng, F.[Feng],
Dense-Localizing Audio-Visual Events in Untrimmed Videos: A Large-Scale Benchmark and Baseline,
CVPR23(22942-22951)
IEEE DOI 2309
BibRef

Rodin, I.[Ivan], Furnari, A.[Antonino], Mavroeidis, D.[Dimitrios], Farinella, G.M.[Giovanni Maria],
Untrimmed Action Anticipation,
CIAP22(III:337-348).
Springer DOI 2205
BibRef

Liu, Y.[Yuan], Chen, J.Y.[Jing-Yuan], Chen, Z.F.[Zhen-Fang], Deng, B.[Bing], Huang, J.Q.[Jian-Qiang], Zhang, H.W.[Han-Wang],
The Blessings of Unlabeled Background in Untrimmed Videos,
CVPR21(6172-6181)
IEEE DOI 2111
Location awareness, Training, Visualization, Smoothing methods, Computational modeling BibRef

Alcázar, J.L.[Juan León], Heilbron, F.C.[Fabian Caba], Mai, L.[Long], Perazzi, F.[Federico], Lee, J.Y.[Joon-Young], Arbeláez, P.[Pablo], Ghanem<", B.[Bernard], /A1>,
APES: Audiovisual Person Search in Untrimmed Video,
MULA21(1720-1729)
IEEE DOI 2109
Visualization, Annotations, Streaming media, Benchmark testing, Search problems BibRef

Zhang, D., Dai, X., Wang, Y.,
METAL: Minimum Effort Temporal Activity Localization in Untrimmed Videos,
CVPR20(3881-3891)
IEEE DOI 2008
Videos, Training, Metals, Testing, Feature extraction, Task analysis, Visualization BibRef

Arnab, A.[Anurag], Sun, C.[Chen], Nagrani, A.[Arsha], Schmid, C.[Cordelia],
Uncertainty-aware Weakly Supervised Action Detection from Untrimmed Videos,
ECCV20(X:751-768).
Springer DOI 2011
BibRef

Gao, M.F.[Ming-Fei], Zhou, Y.B.[Ying-Bo], Xu, R.[Ran], Socher, R.[Richard], Xiong, C.M.[Cai-Ming],
WOAD: Weakly Supervised Online Action Detection in Untrimmed Videos,
CVPR21(1915-1923)
IEEE DOI 2111
Training, Annotations, Scalability, Real-time systems, Generators BibRef

Gao, M.F.[Ming-Fei], Xu, M.Z.[Ming-Ze], Davis, L.S.[Larry S.], Socher, R.[Richard], Xiong, C.M.[Cai-Ming],
StartNet: Online Detection of Action Start in Untrimmed Videos,
ICCV19(5541-5550)
IEEE DOI 2004
feature extraction, gesture recognition, image classification, image colour analysis, Training data BibRef

Bai, R., Zhao, Q., Zhou, S., Li, Y., Zhao, X., Wang, J.,
Continuous Action Recognition and Segmentation in Untrimmed Videos,
ICPR18(2534-2539)
IEEE DOI 1812
Videos, Feature extraction, Motion segmentation, Hidden Markov models, Task analysis, Computer vision BibRef

Gleason, J., Schwarcz, S., Ranjan, R., Castillo, C.D., Chen, J., Chellappa, R.,
Activity Detection in Untrimmed Videos Using Chunk-based Classifiers,
WACVWS20(107-116)
IEEE DOI 2006
Videos, Task analysis, Proposals, Machine learning, Standards BibRef

Gleason, J., Castillo, C.D., Chellappa, R.,
Real-time Detection of Activities in Untrimmed Videos,
WACVWS20(117-125)
IEEE DOI 2006
Videos, Proposals, Cameras, Real-time systems, Training, Object detection, Measurement BibRef

Zhai, C.B.[Chang-Bo], Wang, L.[Le], Zhang, Q.L.[Qi-Lin], Gao, Z.N.[Zhan-Ning], Niu, Z.X.[Zhen-Xing], Zheng, N.N.[Nan-Ning], Hua, G.[Gang],
Action Co-localization in an Untrimmed Video by Graph Neural Networks,
MMMod20(I:555-567).
Springer DOI 2003
BibRef

Rahman, M.A., Laganière, R.,
Single-Stage End-to-End Temporal Activity Detection in Untrimmed Videos,
CRV20(206-213)
IEEE DOI 2006
temporal activity detection, activity recognition, single-stage detection, 3D convolutional network BibRef

Yoon, S.[Sunjae], Koo, G.[Gwanhyeong], Kim, D.[Dahyun], Yoo, C.D.[Chang D.],
SCANet: Scene Complexity Aware Network for Weakly-Supervised Video Moment Retrieval,
ICCV23(13530-13540)
IEEE DOI 2401
BibRef

Yoon, S.[Sunjae], Hong, J.W.[Ji Woo], Yoon, E.[Eunseop], Kim, D.[Dahyun], Kim, J.Y.[Jun-Yeong], Yoon, H.S.[Hee Suk], Yoo, C.D.[Chang D.],
Selective Query-Guided Debiasing for Video Corpus Moment Retrieval,
ECCV22(XXXVI:185-200).
Springer DOI 2211
BibRef

Yoon, S.[Sunjae], Kim, D.[Dahyun], Hong, J.W.[Ji Woo], Kim, J.Y.[Jun-Yeong], Kim, K.[Kookhoi], Yoo, C.D.[Chang D.],
Weakly-Supervised Moment Retrieval Network for Video Corpus Moment Retrieval,
ICIP21(534-538)
IEEE DOI 2201
Training, Image processing, Natural languages, Benchmark testing, Proposals, Multi-modal video corpus moment retrieval, Weakly-supervised learning BibRef

Ma, M.[Minuk], Yoon, S.[Sunjae], Kim, J.Y.[Jun-Yeong], Lee, Y.J.[Young-Joon], Kang, S.H.[Sung-Hun], Yoo, C.D.[Chang D.],
VLANet: Video-language Alignment Network for Weakly-supervised Video Moment Retrieval,
ECCV20(XXVIII:156-171).
Springer DOI 2011
Localize the temporal moment in untrimmed video specified by natural language query. BibRef

Wu, W., He, D., Tan, X., Chen, S., Wen, S.,
Multi-Agent Reinforcement Learning Based Frame Sampling for Effective Untrimmed Video Recognition,
ICCV19(6221-6230)
IEEE DOI 2004
image classification, image motion analysis, learning (artificial intelligence), Markov processes BibRef

Moltisanti, D.[Davide], Fidler, S.[Sanja], Damen, D.[Dima],
Action Recognition From Single Timestamp Supervision in Untrimmed Videos,
CVPR19(9907-9916).
IEEE DOI 2002
BibRef

Chauhan, J.S., Wang, Y.,
Context-Aware Action Detection in Untrimmed Videos Using Bidirectional LSTM,
CRV18(222-229)
IEEE DOI 1812
Videos, Logic gates, Task analysis, Standards, Mathematical model, Microprocessors, action detection, LSTM, video analysis BibRef

Shou, Z.[Zheng], Pan, J.T.[Jun-Ting], Chan, J.[Jonathan], Miyazawa, K.[Kazuyuki], Mansour, H.[Hassan], Vetro, A.[Anthony], Giro-i-Nieto, X.[Xavier], Chang, S.F.[Shih-Fu],
Online Detection of Action Start in Untrimmed, Streaming Videos,
ECCV18(III: 551-568).
Springer DOI 1810
BibRef

Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Accumulation Methods, Motion Histograms for Human Action Recognition .


Last update:Sep 21, 2026 at 18:29:27