17.1.3.7 Human Action Detection, Human Action Recognition

Yu, T., Wang, L., Da, C., Gu, H., Xiang, S., Pan, C.,
Weakly Semantic Guided Action Recognition,
MultMed(21), No. 10, October 2019, pp. 2504-2517.
IEEE DOI 1910
convolutional neural nets, feature extraction, image classification, image motion analysis, attention model BibRef

Tian, Y.[Yan], Cao, Y.F.[Yi-Fan], Wu, J.C.[Jia-Chen], Hu, W.[Wei], Song, C.[Chao], Yang, T.[Tao],
Multi-cue combination network for action-based video classification,
IET-CV(13), No. 6, September 2019, pp. 542-548.
DOI Link 1911
Both visual and acoustic. BibRef

Adeli, V.[Vida], Fazl-Ersi, E.[Ehsan], Harati, A.[Ahad],
A component-based video content representation for action recognition,
IVC(90), 2019, pp. 103805.
Elsevier DOI 1912
Actionness likelihood, Action recognition, Action components, LSTM, Three-stream convolutional neural network BibRef

Yi, Y.[Yang], Li, A.[Ao], Zhou, X.F.[Xiao-Feng],
Human action recognition based on action relevance weighted encoding,
SP:IC(80), 2020, pp. 115640.
Elsevier DOI 1912
Action recognition, Action relevance, Saliency map, Weighted encoding BibRef

Saremi, M.[Mehrin], Yaghmaee, F.[Farzin],
Probabilistic selection of frames for early action recognition in videos,
MultInfoRetr(8), No. 4, December 2019, pp. 253-257.
Springer DOI 1912
Recognize actions with partial viewing. BibRef

Ji, Y., Zhan, Y., Yang, Y., Xu, X., Shen, F., Shen, H.T.,
A Context Knowledge Map Guided Coarse-to-Fine Action Recognition,
IP(29), 2020, pp. 2742-2752.
IEEE DOI 2001
Human action recognition, multi-modal fusion, coarse-to-fine classification, knowledge map BibRef

Wang, J.Z.[Jin-Zhuo], Wang, W.M.[Wen-Min], Gao, W.[Wen],
Fast and Accurate Action Detection in Videos With Motion-Centric Attention Model,
CirSysVideo(30), No. 1, January 2020, pp. 117-130.
IEEE DOI 2002
Where to look in detail. feature extraction, image classification, image motion analysis, learning (artificial intelligence), neural nets, recurrent neural network BibRef

Chen, X.T.[Xiong-Tao], Wang, W.M.[Wen-Min], Li, W.M.[Wei-Mian], Wang, J.Z.[Jin-Zhuo],
Attention-Based Two-Phase Model for Video Action Detection,
CAIP17(II: 81-93).
Springer DOI 1708
BibRef

Peng, B.[Bo], Lei, J.J.[Jian-Jun], Fu, H.Z.[Hua-Zhu], Zhang, C.Q.[Chang-Qing], Chua, T.S.[Tat-Seng], Li, X.L.[Xue-Long],
Unsupervised Video Action Clustering via Motion-Scene Interaction Constraint,
CirSysVideo(30), No. 1, January 2020, pp. 131-144.
IEEE DOI 2002
image representation, object recognition, pattern clustering, unsupervised learning, video signal processing, subspace representation BibRef

Khowaja, S.A.[Sunder Ali], Lee, S.L.[Seok-Lyong],
Semantic Image Networks for Human Action Recognition,
IJCV(128), No. 2, February 2020, pp. 393-419.
Springer DOI 2002
BibRef

Khan, M.A.[Muhammad Attique], Akram, T.[Tallha], Sharif, M.[Muhammad], Muhammad, N.[Nazeer], Javed, M.Y.[Muhammad Younus], Naqvi, S.R.[Syed Rameez],
Improved strategy for human action recognition: Experiencing a cascaded design,
IET-IPR(14), No. 5, 17 April 2020, pp. 818-829.
DOI Link 2004
BibRef

Han, T.T.[Ting-Ting], Yao, H.X.[Hong-Xun], Xie, W.L.[Wen-Long], Sun, X.S.[Xiao-Shuai], Zhao, S.C.[Si-Cheng], Yu, J.[Jun],
TVENet: Temporal variance embedding network for fine-grained action representation,
PR(103), 2020, pp. 107267.
Elsevier DOI 2005
Fine-grained action representation, temporal variance embedding network (TVENet), action search BibRef

Weng, J.W.[Jun-Wu], Jiang, X.D.[Xu-Dong], Zheng, W.L.[Wei-Long], Yuan, J.S.[Jun-Song],
Early Action Recognition With Category Exclusion Using Policy-Based Reinforcement Learning,
CirSysVideo(30), No. 12, December 2020, pp. 4626-4638.
IEEE DOI 2012
Task analysis, Feature extraction, Convolution, Machine learning, policy-based reinforcement learning BibRef

Afza, F.[Farhat], Khan, M.A.[Muhammad Attique], Sharif, M.[Muhammad], Kadry, S.[Seifedine], Manogaran, G.[Gunasekaran], Saba, T.[Tanzila], Ashraf, I.[Imran], Damaševicius, R.[Robertas],
A framework of human action recognition using length control features fusion and weighted entropy-variances based feature selection,
IVC(106), 2021, pp. 104090.
Elsevier DOI 2102
Pre-processing, Frames fusion, Features extraction, Features fusion, Features selection, Classification BibRef

Cheltha, J.N.[Jeba Nega], Sharma, C.[Chirag], Prashar, D.[Deepak], Khan, A.A.[Arfat Ahmad], Kadry, S.[Seifedine],
Enhanced human motion detection with hybrid RDA-WOA-based RNN and multiple hypothesis tracking for occlusion handling,
IVC(150), 2024, pp. 105234.
Elsevier DOI 2409
Human motion detection, Adapted canny edge detection, Modified mask R-CNN, RNN, Multiple hypothesis tracking, Instance segmentation BibRef

Wang, J.P.[Jin-Peng], Hu, J.G.[Jian-Guo], Li, S.R.[Shi-Ren], Yuan, Z.H.[Zhi-Hao],
Revisiting Hard Example for Action Recognition,
CirSysVideo(31), No. 2, February 2021, pp. 546-556.
IEEE DOI 2102
Motion and spatial cues together. Correlation, Training, Shape, Kernel, Image recognition, temporal sampling BibRef

Kumar, D.[Deepak], Kumar, C.[Chetan], Shao, M.[Ming],
Collaborative knowledge distillation for incomplete multi-view action prediction,
IVC(107), 2021, pp. 104111.
Elsevier DOI 2103
Multi-view, Action prediction, Knowledge distillation, Graph attention BibRef

Shen, Z.W.[Zhong-Wei], Wu, X.J.[Xiao-Jun], Kittler, J.V.[Josef V.],
2D progressive fusion module for action recognition,
IVC(109), 2021, pp. 104122.
Elsevier DOI 2105
Convergence, spatiotemporal modeling, 2D CNN, action recognition BibRef

Weinzaepfel, P.[Philippe], Rogez, G.[Grégory],
Mimetics: Towards Understanding Human Actions Out of Context,
IJCV(129), No. 5, May 2021, pp. 1675-1690.
Springer DOI 2105

See also LCR-Net++: Multi-Person 2D and 3D Pose Detection in Natural Images. BibRef

Wu, L.F.[Li-Fang], Yang, Z.[Zhou], Jian, M.[Meng], Shen, J.L.[Jia-Lie], Yang, Y.C.[Yu-Chen], Lang, X.L.[Xiang-Long],
Global motion estimation with iterative optimization-based independent univariate model for action recognition,
PR(116), 2021, pp. 107925.
Elsevier DOI 2106
Global motion estimation, Iterative optimization, Independent univariate global motion model, Action recognition BibRef

Padilha, R.[Rafael], Andaló, F.A.[Fernanda A.], Lavi, B.[Bahram], Pereira, L.A.M.[Luís A.M.], Rocha, A.[Anderson],
Temporally sorting images from real-world events,
PRL(147), 2021, pp. 212-219.
Elsevier DOI 2106
Temporal ordering, Visual analysis, Event understanding, Event reconstruction BibRef

Cao, C.Q.[Cong-Qi], Li, J.K.[Jia-Kang], Xi, R.P.[Run-Ping], Zhang, Y.N.[Yan-Ning],
Club Ideas and Exertions: Aggregating Local Predictions for Action Recognition,
CirSysVideo(31), No. 6, June 2021, pp. 2247-2259.
IEEE DOI 2106
Feature extraction, Streaming media, Aggregates, Training, Visualization, Task analysis, Optical imaging, Attention, action recognition BibRef

Yoshikawa, Y.[Yuya], Shigeto, Y.[Yutaro], Takeuchi, A.[Akikazu],
MetaVD: A Meta Video Dataset for enhancing human action recognition datasets,
CVIU(212), 2021, pp. 103276.
Elsevier DOI 2110
Human action recognition, Video datasets BibRef

Yoshikawa, Y.[Yuya], Shigeto, Y.[Yutaro], Shimbo, M.[Masashi], Takeuchi, A.[Akikazu],
Action class relation detection and classification across multiple video datasets,
PRL(173), 2023, pp. 93-100.
Elsevier DOI 2310
Relation prediction, MetaVD, Human action recognition, Multi-modal classification BibRef

Yenduri, S.[Sravani], Perveen, N.[Nazil], Chalavadi, V.[Vishnu], Mohan, C.K.[C. Krishna],
Fine-grained action recognition using dynamic kernels,
PR(122), 2022, pp. 108282.
Elsevier DOI 2112
Fine-grained action recognition, Spatio-temporal features, Gaussian mixture model, Dynamic kernels BibRef

Chen, W.J.[Wan-Jun], Liu, L.[Long], Lin, G.F.[Guang-Feng], Chen, Y.J.[Ya-Jun], Wang, J.[Jing],
Class structure-aware adversarial loss for cross-domain human action recognition,
IET-IPR(15), No. 14, 2021, pp. 3425-3432.
DOI Link 2112
BibRef

Moniruzzaman, M.[Md], Yin, Z.Z.[Zhao-Zheng], He, Z.H.[Zhi-Hai], Qin, R.[Ruwen], Leu, M.C.[Ming C.],
Human Action Recognition by Discriminative Feature Pooling and Video Segment Attention Model,
MultMed(24), 2022, pp. 689-701.
IEEE DOI 2202
Feature extraction, Annotations, Training, Image recognition, Task analysis, Action recognition, attentional pooling, weakly-supervised BibRef

Kurban, O.C.[Onur Can], Calik, N.[Nurullah], Yildirim, T.[Tülay],
Human and action recognition using adaptive energy images,
PR(127), 2022, pp. 108621.
Elsevier DOI 2205
Motion recognition, Human recognition, Correlation coefficients, Deep learning, Behavioral biometrics BibRef

Liu, Y.Z.[Yuan-Zhong], Yuan, J.S.[Jun-Song], Tu, Z.G.[Zhi-Gang],
Motion-Driven Visual Tempo Learning for Video-Based Action Recognition,
IP(31), 2022, pp. 4104-4116.
IEEE DOI 2206

WWW Link. Code, Action Recognition. Feature extraction, Visualization, Correlation, Dynamics, Semantics, Spatiotemporal phenomena, Action recognition, visual tempo, temporal correlation module BibRef

Li, Z.[Zhe], Zhang, H.B.[Hong-Bo], Zhang, M.H.[Miao-Hui], Lei, Q.[Qing], Du, J.X.[Ji-Xiang],
Late feature supplement network for early action prediction,
IVC(125), 2022, pp. 104519.
Elsevier DOI 2208
Early action prediction, Early clip, Late clip, Feature supplement, Observation ratio BibRef

E-Elahi, G.M.M.[G. M. Mashrur], Yang, Y.H.[Yee-Hong],
Online temporal classification of human action using action inference graph,
PR(132), 2022, pp. 108972.
Elsevier DOI 2209
Online temporal classification, Action recognition, Action detection, Action inference graph BibRef

Yao, Z.Y.[Zhi-Yu], Wang, Y.B.[Yun-Bo], Wang, J.M.[Jian-Min], Yu, P.S.[Philip S.], Long, M.S.[Ming-Sheng],
VideoDG: Generalizing Temporal Relations in Videos to Novel Domains,
PAMI(44), No. 11, November 2022, pp. 7989-8004.
IEEE DOI 2210
Videos, Training, Adaptation models, Transfer learning, Spatiotemporal phenomena, Benchmark testing, Robustness, video action recognition 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

Shang, J.H.[Jia-Hui], Wei, P.[Ping], Li, H.[Huan], Zheng, N.N.[Nan-Ning],
Multi-scale interaction transformer for temporal action proposal generation,
IVC(129), 2023, pp. 104589.
Elsevier DOI 2301
Temporal action proposal generation, Transformer, Multi-scale interaction, Feature pyramids BibRef

Yang, J.[Jin], Wei, P.[Ping], Ren, Z.Y.[Zi-Yang], Zheng, N.N.[Nan-Ning],
Gated Multi-Scale Transformer for Temporal Action Localization,
MultMed(26), 2024, pp. 5705-5717.
IEEE DOI 2404
Logic gates, Transformers, Location awareness, Feature extraction, Proposals, Context modeling, Information filters, video understanding BibRef

Lin, J.[Jie], Mu, Z.K.[Ze-Kun], Zhao, T.Q.[Tian-Qing], Zhang, H.L.[Han-Lin], Yang, X.Y.[Xin-Yu], Zhao, P.[Peng],
Action density based frame sampling for human action recognition in videos,
JVCIR(90), 2023, pp. 103740.
Elsevier DOI 2301
Action recognition, Frame sampling, Action density, Neural network BibRef

Zhang, Y.H.[Yin-Huan], Xiao, Q.[Qinkun], Liu, X.[Xing], Wei, Y.Q.[Yong-Quan], Chu, C.Q.[Chao-Qin], Xue, J.Y.[Jing-Yun],
Multi-modal fusion method for human action recognition based on IALC,
IET-IPR(17), No. 2, 2023, pp. 388-400.
DOI Link 2302
BibRef

Lee, S.[Sumin], Eun, H.[Hyunjun], Moon, J.[Jinyoung], Choi, S.[Seokeon], Kim, Y.[Yoonhyung], Jung, C.[Chanho], Kim, C.[Changick],
Learning to Discriminate Information for Online Action Detection: Analysis and Application,
PAMI(45), No. 5, May 2023, pp. 5918-5934.
IEEE DOI 2304
Streaming media, Task analysis, Proposals, Recurrent neural networks, Predictive models, Logic gates, long short-term memory (LSTM) BibRef

Lee, S.[Sumin], Woo, S.[Sangmin], Park, Y.[Yeonju], Nugroho, M.A.[Muhammad Adi], Kim, C.[Changick],
Modality Mixer for Multi-modal Action Recognition,
WACV23(3297-3306)
IEEE DOI 2302
Mixers, Algorithms: Video recognition and understanding (tracking, Vision + language and/or other modalities BibRef

Liu, Z.[Zhen], Cheng, Q.[Qin], Song, C.Q.[Cheng-Qun], Cheng, J.[Jun],
Cross-scale cascade transformer for multimodal human action recognition,
PRL(168), 2023, pp. 17-23.
Elsevier DOI 2304
Action recognition, Multimodal fusion, Transformer, Two-stream, RGB-D sequences BibRef

Yoo, H.S.[Hong-Sang], Li, H.P.[Hao-Peng], Ke, Q.H.[Qiu-Hong], Liu, L.C.[Liang-Chen], Zhang, R.[Rui],
Precondition and effect reasoning for action recognition,
CVIU(232), 2023, pp. 103691.
Elsevier DOI 2305
BibRef

Lin, W.[Wei], Ding, X.H.[Xing-Hao], Huang, Y.[Yue], Zeng, H.Q.[Huan-Qiang],
Self-Supervised Video-Based Action Recognition With Disturbances,
IP(32), 2023, pp. 2493-2507.
IEEE DOI 2305
Videos, Semantics, Task analysis, Visualization, Character recognition, Optical imaging, Image recognition, disturbances BibRef

Lin, W.[Wei], Liu, X.Y.[Xiao-Yu], Zhuang, Y.H.[Yi-Hong], Ding, X.H.[Xing-Hao], Tu, X.T.[Xiao-Tong], Huang, Y.[Yue], Zeng, H.Q.[Huan-Qiang],
Unsupervised Video-Based Action Recognition With Imagining Motion and Perceiving Appearance,
CirSysVideo(33), No. 5, May 2023, pp. 2245-2258.
IEEE DOI 2305
Videos, Feature extraction, Image recognition, Task analysis, Character recognition, Data mining, Action recognition, imagine BibRef

Chen, Y.T.[Ya-Tong], Ge, H.W.[Hong-Wei], Liu, Y.X.[Yu-Xuan], Cai, X.Y.[Xin-Ye], Sun, L.[Liang],
AGPN: Action Granularity Pyramid Network for Video Action Recognition,
CirSysVideo(33), No. 8, August 2023, pp. 3912-3923.
IEEE DOI 2308
Feature extraction, Fuses, Data mining, Computational modeling, Convolution, Visualization, Aggregates, Video action recognition, multi-granularity BibRef

Park, Y.[Yeonju], Woo, S.[Sangmin], Lee, S.[Sumin], Nugroho, M.A.[Muhammad Adi], Kim, C.[Changick],
Cross-modal alignment and translation for missing modality action recognition,
CVIU(236), 2023, pp. 103805.
Elsevier DOI 2310
Video action recognition, Multi-modal learning, Missing modality, Contrastive learning, Feature translation BibRef

Gan, M.G.[Ming-Gang], Zhang, Y.[Yan],
Temporal Attention-Pyramid Pooling for Temporal Action Detection,
MultMed(25), 2023, pp. 3799-3810.
IEEE DOI 2310
BibRef

Mitsuzumi, Y.[Yu], Irie, G.[Go], Kimura, A.[Akisato], Nakazawa, A.[Atsushi],
Phase Randomization: A data augmentation for domain adaptation in human action recognition,
PR(146), 2024, pp. 110051.
Elsevier DOI 2311
Domain adaptation, Human action recognition, Time-series data BibRef

Ma, Y.J.[Yu-Jun], Wang, R.[Ruili],
Relative-position embedding based spatially and temporally decoupled Transformer for action recognition,
PR(145), 2024, pp. 109905.
Elsevier DOI 2311
Transformer, Relative-position embedding, Spatial-temporal features, Subsampling BibRef

Zhang, Y.[Yu], Chen, Z.J.[Zheng-Jie], Xu, T.Y.[Tian-Yu], Zhao, J.J.[Jun-Jie], Mi, S.[Siya], Geng, X.[Xin], Zhang, M.L.[Min-Ling],
Temporal segment dropout for human action video recognition,
PR(146), 2024, pp. 109985.
Elsevier DOI 2311
Action recognition, Temporal regularization, Temporal segment dropout BibRef

Chen, J.H.[Jing-Hong], Jin, Z.H.[Zhi-Hao], Wang, Q.C.[Qi-Cong], Meng, H.Y.[Hong-Ying],
Self-Supervised 3D Behavior Representation Learning Based on Homotopic Hyperbolic Embedding,
IP(32), 2023, pp. 6061-6074.
IEEE DOI 2311
BibRef

Zhang, Y.[Yu], Zhao, J.J.[Jun-Jie], Chen, Z.J.[Zheng-Jie], Mi, S.[Siya], Zhu, H.Y.[Hong-Yuan], Geng, X.[Xin],
A Closer Look at Video Sampling for Sequential Action Recognition,
CirSysVideo(33), No. 12, December 2023, pp. 7503-7514.
IEEE DOI 2312
BibRef

Wang, J.[Junyan], Jiang, Y.Q.[Yi-Qi], Long, Y.[Yang], Sun, X.[Xiuyu], Pagnucco, M.[Maurice], Song, Y.[Yang],
Deconfounding Causal Inference for Zero-Shot Action Recognition,
MultMed(26), 2024, pp. 3976-3986.
IEEE DOI 2402
Semantics, Training, Task analysis, Feature extraction, Visualization, Training data, Zero-shot learning, causal inference BibRef

Ye, K.[Kun], Wu, S.[Sheng], Cai, Y.B.[Yong-Bin], Zhou, L.[Lang], Xiao, L.J.[Li-Jun], Zhang, X.B.[Xue-Bo], Zheng, Z.[Zheng], Lin, J.Q.[Jia-Qing],
Transfer-Learning-Based Human Activity Recognition Using Antenna Array,
RS(16), No. 5, 2024, pp. 845.
DOI Link 2403
BibRef

Olivas-Padilla, B.E.[Brenda Elizabeth], Manitsaris, S.[Sotiris], Glushkova, A.[Alina],
Explainable AI in human motion: A comprehensive approach to analysis, modeling, and generation,
PR(151), 2024, pp. 110418.
Elsevier DOI 2404
Human movement analysis, Explainable models, State-space modeling, Wearable sensors, Gesture recognition BibRef

Mou, Y.T.[Yu-Ting], Jiang, X.H.[Xing-Hao], Xu, K.[Ke], Sun, T.F.[Tan-Feng], Wang, Z.P.[Ze-Peng],
Compressed Video Action Recognition With Dual-Stream and Dual-Modal Transformer,
CirSysVideo(34), No. 5, May 2024, pp. 3299-3312.
IEEE DOI 2405
Feature extraction, Transformers, Optical flow, Decoding, Streaming media, Semantics, Dams, Compressed video, action recognition BibRef

Liu, W.X.[Wen-Xuan], Jia, X.M.[Xue-Mei], Zhong, X.[Xian], Jiang, K.[Kui], Yu, X.H.[Xiao-Han], Ye, M.[Mang],
Dynamic and static mutual fitting for action recognition,
PR(157), 2025, pp. 110948.
Elsevier DOI 2409
Dynamic temporal-aware erasing, Mutual fitting, Static augmentation, Pseudo-occlusion, Action recognition BibRef

Lin, J.T.[Jin-Tao], Liu, Z.Y.[Zhao-Yang], Wang, W.H.[Wen-Hai], Wu, W.[Wayne], Wang, L.M.[Li-Min],
VLG: General Video Recognition with Web Textual Knowledge,
IJCV(132), No. 10, October 2024, pp. 4792-4817.
Springer DOI 2410
BibRef

Li, T.[Tankun], Chan, K.L.[Kwok Leung], Tjahjadi, T.[Tardi],
A learnable motion preserving pooling for action recognition,
IVC(151), 2024, pp. 105278.
Elsevier DOI 2411
Action recognition, Video classification, Temporal pooling BibRef

Wang, Q.[Qi], Xu, Z.[Zhou], Lin, Y.M.[Yu-Ming], Ye, J.T.[Jing-Tao], Li, H.S.[Hong-Sheng], Zhu, G.M.[Guang-Ming], Shah, S.A.A.[Syed Afaq Ali], Bennamoun, M.[Mohammed], Zhang, L.[Liang],
Dailydvs-200: A Comprehensive Benchmark Dataset for Event-based Action Recognition,
ECCV24(LXXXIV: 55-72).
Springer DOI 2412
BibRef

Garg, P.[Prachi], Joseph, K.J., Balasubramanian, V.N.[Vineeth N.], Camgo, N.C.[Necati Cihan], Wan, C.[Chengde], Kin, K.[Kenrick], Si, W.G.[Wei-Guang], Ma, S.[Shugao], de la Torre, F.[Fernando],
Poet: Prompt Offset Tuning for Continual Human Action Adaptation,
ECCV24(LXIV: 436-455).
Springer DOI 2412
BibRef

Dave, I.R.[Ishan Rajendrakumar], Rizve, M.N.[Mamshad Nayeem], Shah, M.[Mubarak],
Finepseudo: Improving Pseudo-labelling Through Temporal-alignablity for Semi-supervised Fine-grained Action Recognition,
ECCV24(VIII: 389-408).
Springer DOI 2412
BibRef

Dinai, Y.[Yonatan], Raviv, A.[Avraham], Harel, N.[Nimrod], Kim, D.[Donghoon], Goldin, I.[Ishay], Zehngut, N.[Niv],
TAPS: Temporal Attention-based Pruning and Scaling for Efficient Video Action Recognition,
ACCV24(III: 422-438).
Springer DOI 2412
BibRef

Diko, A.[Anxhelo], Avola, D.[Danilo], Prenkaj, B.[Bardh], Fontana, F.[Federico], Cinque, L.[Luigi],
Semantically Guided Representation Learning For Action Anticipation,
ECCV24(XXVIII: 448-466).
Springer DOI 2412
BibRef

Liu, Z.H.[Zhi-Hao], Zhang, Y.[Yi], Huang, W.H.[Wen-Hui], Liu, Y.[Yan], Pu, M.Y.[Meng-Yang], Deng, C.[Chao], Feng, J.[Junlan],
Learning Temporal Cues for Fine-Grained Action Recognition,
ICIP24(2473-2479)
IEEE DOI 2411
Image recognition, Transformers, Feature extraction, Decoding, Action recognition, Video understanding, Fine-grained feature extraction BibRef

Fahim, M.A.N.I.[Masud An-Nur Islam], Innat, M.[Mohammed], Boutellier, J.[Jani],
ST2ST: Self-Supervised Test-time Adaptation for Video Action Recognition,
MAT24(1057-1066)
IEEE DOI 2410
Adaptation models, Rain, Semantics, Training data, Artificial neural networks, Predictive models, Transformers, TTA, Action recogniton BibRef

Li, Y.L.[Yong-Lu], Wu, X.Q.[Xiao-Qian], Liu, X.P.[Xin-Peng], Wang, Z.[Zehao], Dou, Y.M.[Yi-Ming], Ji, Y.K.[Yi-Kun], Zhang, J.[Junyi], Li, Y.X.[Yi-Xing], Lu, X.D.[Xu-Dong], Tan, J.[Jingru], Lu, C.[Cewu],
From Isolated Islands to Pangea: Unifying Semantic Space for Human Action Understanding,
CVPR24(16582-16592)
IEEE DOI Code:
WWW Link. 2410
Bridges, Codes, Databases, Semantics, Transfer learning, Taxonomy, human action understanding BibRef

Zhu, P.Y.[Pei-Yuan], Zhao, S.J.[Sheng-Jie], Han, F.X.[Feng-Xia], Deng, H.[Hao],
BEAVP: A Bidirectional Enhanced Adversarial Model for Video Prediction,
FG24(1-8)
IEEE DOI 2408
Face recognition, Stochastic processes, Gesture recognition, Predictive models, Behavioral sciences BibRef

Xian, R.Q.[Rui-Qi], Wang, X.[Xijun], Kothandaraman, D.[Divya], Manocha, D.[Dinesh],
PMI Sampler: Patch Similarity Guided Frame Selection For Aerial Action Recognition,
WACV24(6967-6976)
IEEE DOI Code:
WWW Link. 2404
Adaptation models, Codes, Motion segmentation, Cameras, Motion measurement, Spatial resolution, Algorithms, Robotics BibRef

Xian, R.Q.[Rui-Qi], Wang, X.J.[Xi-Jun], Manocha, D.[Dinesh],
MITFAS: Mutual Information based Temporal Feature Alignment and Sampling for Aerial Video Action Recognition,
WACV24(6611-6620)
IEEE DOI Code:
WWW Link. 2404
Codes, Computational modeling, X3D, Autonomous aerial vehicles, Sampling methods, Mutual information, Algorithms, Robotics BibRef

Zhang, H.[Haosong], Leong, M.C.[Mei Chee], Li, L.Y.[Li-Yuan], Lin, W.S.[Wei-Si],
PeVL: Pose-Enhanced Vision-Language Model for Fine-Grained Human Action Recognition,
CVPR24(18857-18867)
IEEE DOI 2410
Adaptation models, Visualization, Semantics, Contrastive learning, Computer architecture, Performance gain BibRef

Zhang, H.[Haosong], Leong, M.C.[Mei Chee], Li, L.Y.[Li-Yuan], Lin, W.S.[Wei-Si],
PGVT: Pose-Guided Video Transformer for Fine-Grained Action Recognition,
WACV24(6631-6642)
IEEE DOI 2404
Training, Adaptation models, Visualization, Image recognition, Costs, Semantics, Algorithms, Video recognition and understanding, Vision + language and/or other modalities BibRef

Ragusa, F.[Francesco], Leonardi, R.[Rosario], Mazzamuto, M.[Michele], Bonanno, C.[Claudia], Scavo, R.[Rosario], Furnari, A.[Antonino], Farinella, G.M.[Giovanni Maria],
ENIGMA-51: Towards a Fine-Grained Understanding of Human Behavior in Industrial Scenarios,
WACV24(4537-4547)
IEEE DOI Code:
WWW Link. 2404
Systematics, Video sequences, Oscilloscopes, Benchmark testing, Maintenance engineering, Natural language processing, Algorithms, Video recognition and understanding BibRef

Li, H.X.[Hao-Xin], Liu, Y.[Yuan], Zhang, H.W.[Han-Wang], Li, B.Y.[Bo-Yang],
Mitigating and Evaluating Static Bias of Action Representations in the Background and the Foreground,
ICCV23(19854-19866)
IEEE DOI Code:
WWW Link. 2401
BibRef

Chen, Y.F.[Yi-Fei], Chen, D.P.[Da-Peng], Liu, R.J.[Rui-Jin], Li, H.[Hao], Peng, W.[Wei],
Video Action Recognition with Attentive Semantic Units,
ICCV23(10136-10146)
IEEE DOI 2401
BibRef

Plizzari, C.[Chiara], Perrett, T.[Toby], Caputo, B.[Barbara], Damen, D.[Dima],
What can a cook in Italy teach a mechanic in India? Action Recognition Generalisation Over Scenarios and Locations,
ICCV23(13610-13620)
IEEE DOI Code:
WWW Link. 2401
BibRef

Barquero, G.[German], Escalera, S.[Sergio], Palmero, C.[Cristina],
BeLFusion: Latent Diffusion for Behavior-Driven Human Motion Prediction,
ICCV23(2317-2327)
IEEE DOI 2401
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Geara, C.[Carla], Setkov, A.[Aleksandr], Orcesi, A.[Astrid], Luvison, B.[Bertrand],
Feature Space Data Augmentation for Viewpoint-Robust Action Recognition in Videos,
ICIP23(585-589)
IEEE DOI 2312
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Cen, J.[Jun], Zhang, S.W.[Shi-Wei], Wang, X.[Xiang], Pei, Y.X.[Yi-Xuan], Qing, Z.W.[Zhi-Wu], Zhang, Y.Y.[Ying-Ya], Chen, Q.F.[Qi-Feng],
Enlarging Instance-specific and Class-specific Information for Open-set Action Recognition,
CVPR23(15295-15304)
IEEE DOI 2309
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Gulshad, S.[Sadaf], Long, T.[Teng], van Noord, N.[Nanne],
Hierarchical Explanations for Video Action Recognition,
XAI4CV23(3703-3708)
IEEE DOI 2309
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Zhao, C.[Chen], Du, D.W.[Da-Wei], Hoogs, A.[Anthony], Funk, C.[Christopher],
Open Set Action Recognition via Multi-Label Evidential Learning,
CVPR23(22982-22991)
IEEE DOI 2309
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Tsai, W.L.[Wei Lun], Lin, J.J.[Jacob J.], Hsieh, S.H.[Shang-Hsien],
Generating Construction Safety Observations via Clip-based Image-language Embedding,
CVCivil22(366-381).
Springer DOI 2304
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Peng, H.W.[Huai-Wei], Tseng, Y.C.[Yu-Chee],
Multi-Scale Motion-Aware Module for Video Action Recognition,
ACVR22(589-606).
Springer DOI 2304
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Byrne, J.[Jeffrey], Castañón, G.[Greg], Li, Z.H.[Zhong-Heng], Ettinger, G.[Gil],
Fine-grained Activities of People Worldwide,
WACV23(3307-3318)
IEEE DOI 2302
Visualization, Ethics, Benchmark testing, Activity recognition, Data collection, Mobile applications, ethical computer vision BibRef

Du, D.W.[Da-Wei], Shringi, A.[Ameya], Hoogs, A.J.[Anthony J.], Funk, C.[Christopher],
Reconstructing Humpty Dumpty: Multi-feature Graph Autoencoder for Open Set Action Recognition,
WACV23(3360-3369)
IEEE DOI 2302
Semantics, Classification algorithms, Algorithms: Video recognition and understanding. BibRef

Zhong, Z.Y.[Ze-Yun], Schneider, D.[David], Voit, M.[Michael], Stiefelhagen, R.[Rainer], Beyerer, J.[Jürgen],
Anticipative Feature Fusion Transformer for Multi-Modal Action Anticipation,
WACV23(6057-6066)
IEEE DOI 2302
Computational modeling, Feature extraction, Transformers, Ensemble learning, Task analysis, Vision + language and/or other modalities BibRef

Huang, R.F.[Rui-Feng], Chen, C.[Chong], Cheng, R.[Rui], Zhang, Y.[Ying], Zhu, J.B.[Jia-Bing],
Human Action Recognition Based on Three-Stream Network with Frame Sequence Features,
ICIVC22(37-44)
IEEE DOI 2301
Training, Image recognition, Computational modeling, Neural networks, Multilayer perceptrons, Feature extraction, HMDB51 BibRef

Foo, L.G.[Lin Geng], Li, T.J.[Tian-Jiao], Rahmani, H.[Hossein], Ke, Q.H.[Qiu-Hong], Liu, J.[Jun],
ERA: Expert Retrieval and Assembly for Early Action Prediction,
ECCV22(XXXIV:670-688).
Springer DOI 2211
BibRef

Liu, Q.Y.[Qin-Ying], Wang, Z.[Zilei],
Collaborating Domain-Shared and Target-Specific Feature Clustering for Cross-domain 3D Action Recognition,
ECCV22(IV:137-155).
Springer DOI 2211
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Li, J.F.[Jie-Feng], Bian, S.Y.[Si-Yuan], Xu, C.[Chao], Liu, G.[Gang], Yu, G.[Gang], Lu, C.W.[Ce-Wu],
D&D: Learning Human Dynamics from Dynamic Camera,
ECCV22(V:479-496).
Springer DOI 2211
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Yang, J.W.[Jie-Wen], Dong, X.B.[Xing-Bo], Liu, L.J.[Liu-Jun], Zhang, C.[Chao], Shen, J.J.[Jia-Jun], Yu, D.H.[Da-Hai],
Recurring the Transformer for Video Action Recognition,
CVPR22(14043-14053)
IEEE DOI 2210
Representation learning, Visualization, Memory management, Video sequences, Graphics processing units, Logic gates, Machine learning BibRef

Liang, Z.X.[Zi-Xi], Chen, J.J.[Jia-Jun], Chen, R.[Rui], Zheng, B.B.[Bing-Bing], Zhou, M.Y.[Ming-Yue], Gao, H.[Huaien], Lin, S.[Shan],
Domain Adaptable Normalization for Semi-Supervised Action Recognition in the Dark,
UG22(4250-4257)
IEEE DOI 2210
Adaptation models, Costs, Surveillance, Semisupervised learning BibRef

Chen, Z.[Zhi], Fan, Z.J.[Zi-Jun], Li, Y.J.[Yong-Jie], Gao, H.[Huaien], Lin, S.[Shan],
Z-Domain Entropy Adaptable Flex for Semi-supervised Action Recognition in the Dark,
UG22(4258-4265)
IEEE DOI 2210
Flexible printed circuits, Surveillance, Neural networks, Estimation, Feature extraction BibRef

Guo, X.[Xi], Wu, W.[Wei], Wang, D.L.[Dong-Liang], Su, J.[Jing], Su, H.S.[Hai-Sheng], Gan, W.H.[Wei-Hao], Huang, J.[Jian], Yang, Q.[Qin],
Learning Video Representations of Human Motion from Synthetic Data,
CVPR22(20165-20175)
IEEE DOI 2210
Representation learning, Pipelines, Games, Animation, Data mining, Action and event recognition, Video analysis and understanding BibRef

Mazzeo, P.L.[Pier Luigi], Spagnolo, P.[Paolo], Fasano, M.[Matteo], Distante, C.[Cosimo],
Human Action Recognition with Transformers,
CIAP22(III:230-241).
Springer DOI 2205
BibRef

Jenni, S.[Simon], Jin, H.L.[Hai-Lin],
Time-Equivariant Contrastive Video Representation Learning,
ICCV21(9950-9960)
IEEE DOI 2203
Representation learning, Dynamics, Benchmark testing, Distortion, Task analysis, Manipulator dynamics, Representation learning, Video analysis and understanding BibRef

Zhang, X.[Xing], Wu, Z.[Zuxuan], Weng, Z.[Zejia], Fu, H.Z.[Hua-Zhu], Chen, J.J.[Jing-Jing], Jiang, Y.G.[Yu-Gang], Davis, L.S.[Larry S.],
VideoLT: Large-scale Long-tailed Video Recognition,
ICCV21(7940-7949)
IEEE DOI 2203

WWW Link. Training, Knowledge engineering, Adaptation models, Image recognition, Codes, Computational modeling, Recognition and classification BibRef

Kim, D.H.[Dong-Hyun], Tsai, Y.H.[Yi-Hsuan], Zhuang, B.B.[Bing-Bing], Yu, X.[Xiang], Sclaroff, S.[Stan], Saenko, K.[Kate], Chandraker, M.[Manmohan],
Learning Cross-Modal Contrastive Features for Video Domain Adaptation,
ICCV21(13598-13607)
IEEE DOI 2203
Design methodology, Benchmark testing, Task analysis, Optical flow, Videos, Action and behavior recognition, Representation learning, Video analysis and understanding BibRef

Chung, J.[Jihoon], Wuu, C.H.[Cheng-Hsin], Yang, H.R.[Hsuan-Ru], Tai, Y.W.[Yu-Wing], Tang, C.K.[Chi-Keung],
HAA500: Human-Centric Atomic Action Dataset with Curated Videos,
ICCV21(13445-13454)
IEEE DOI 2203
Training, Deep learning, Annotations, Scalability, Predictive models, Spatiotemporal phenomena, Action and behavior recognition, Datasets and evaluation BibRef

Li, J.M.[Jia-Man], Villegas, R.[Ruben], Ceylan, D.[Duygu], Yang, J.M.[Ji-Mei], Kuang, Z.F.[Zheng-Fei], Li, H.[Hao], Zhao, Y.J.[Ya-Jie],
Task-Generic Hierarchical Human Motion Prior using VAEs,
3DV21(771-781)
IEEE DOI 2201
Training, Interpolation, Motion estimation, Pose estimation, Predictive models, Animation BibRef

Neimark, D.[Daniel], Bar, O.[Omri], Zohar, M.[Maya], Asselmann, D.[Dotan],
Video Transformer Network,
CVEU21(3156-3165)
IEEE DOI 2112

WWW Link. Code, Video Recognition. Solid modeling, Runtime, Computational modeling, Video sequences, Machine learning, Benchmark testing BibRef

Hsiao, J.H.[Jen-Hao], Li, Y.K.[Yi-Kang], Ho, C.[Chiuman],
Language-guided Multi-Modal Fusion for Video Action Recognition,
CLVL21(3151-3155)
IEEE DOI 2112
Training, Visualization, Fuses, Benchmark testing, Noise measurement BibRef

Fernando, B.[Basura], Herath, S.[Samitha],
Anticipating human actions by correlating past with the future with Jaccard similarity measures,
CVPR21(13219-13228)
IEEE DOI 2111
Deep learning, Correlation, Loss measurement, Task analysis BibRef

Wang, Z.W.[Zheng-Wei], She, Q.[Qi], Smolic, A.[Aljosa],
ACTION-Net: Multipath Excitation for Action Recognition,
CVPR21(13209-13218)
IEEE DOI 2111
Adaptation models, Codes, Target recognition, Convolution, Computational modeling BibRef

Zhou, J.M.[Jia-Ming], Lin, K.Y.[Kun-Yu], Li, H.X.[Hao-Xin], Zheng, W.S.[Wei-Shi],
Graph-based High-order Relation Modeling for Long-term Action Recognition,
CVPR21(8980-8989)
IEEE DOI 2111
Visualization, Computational modeling, Semantics, Task analysis BibRef

Punnakkal, A.R.[Abhinanda R.], Chandrasekaran, A.[Arjun], Athanasiou, N.[Nikos], Quirós-Ramírez, A.[Alejandra], Black, M.J.[Michael J.],
BABEL: Bodies, Action and Behavior with English Labels,
CVPR21(722-731)
IEEE DOI 2111

WWW Link. Code, Human Action. Location awareness, Solid modeling, Motion segmentation, Semantics, Benchmark testing BibRef

Li, T.J.[Tian-Jiao], Liu, J.[Jun], Zhang, W.[Wei], Ni, Y.[Yun], Wang, W.Q.[Wen-Qian], Li, Z.H.[Zhi-Heng],
UAV-Human: A Large Benchmark for Human Behavior Understanding with Unmanned Aerial Vehicles,
CVPR21(16261-16270)
IEEE DOI 2111
Pose estimation, Video sequences, Lighting, Benchmark testing, Distortion, Unmanned aerial vehicles BibRef

Chen, R.[Rui], Chen, J.J.[Jia-Jun], Liang, Z.X.[Zi-Xi], Gao, H.[Huaien], Lin, S.[Shan],
DarkLight Networks for Action Recognition in the Dark,
UG21(846-852)
IEEE DOI 2109
Fuses, Surveillance, Neural networks, Lighting, Feature extraction BibRef

Hira, S.[Sanchit], Das, R.[Ritwik], Modi, A.[Abhinav], Pakhomov, D.[Daniil],
Delta Sampling R-BERT for limited data and low-light action recognition,
UG21(853-862)
IEEE DOI 2109
Training, Deep learning, Technological innovation, Schedules, Pattern recognition BibRef

Garcia, N.C.[Nuno Cruz], Bargal, S.A.[Sarah Adel], Ablavsky, V.[Vitaly], Morerio, P.[Pietro], Murino, V.[Vittorio], Sclaroff, S.[Stan],
Distillation Multiple Choice Learning for Multimodal Action Recognition,
WACV21(2754-2763)
IEEE DOI 2106
Training, Knowledge engineering, Benchmark testing BibRef

Wang, Y.[Yang], Bertasius, G.[Gedas], Oh, T.H.[Tae-Hyun], Gupta, A.[Abhinav], Hoai, M.[Minh], Torresani, L.[Lorenzo],
Supervoxel Attention Graphs for Long-Range Video Modeling,
WACV21(155-166)
IEEE DOI 2106
Convolution, Computational modeling, Semantics, Cognition, Spatiotemporal phenomena BibRef

Wu, W.[Wei], Yu, J.[Jiale],
An Improved Bilinear Pooling Method for Image-Based Action Recognition,
ICPR21(8578-8583)
IEEE DOI 2105
Visualization, Image recognition, Semantics, Manuals, Interference, Feature extraction, action recognition, mask aggregation BibRef

Li, B.[Bing], Kong, L.T.[Long-Teng], Zhang, D.M.[Dong-Ming], Bao, X.G.[Xiu-Guo], Huang, D.[Di], Wang, Y.H.[Yun-Hong],
Towards Practical Compressed Video Action Recognition: A Temporal Enhanced Multi-Stream Network,
ICPR21(3744-3750)
IEEE DOI 2105
Databases, Dynamics, Jitter, Forecasting BibRef

Pan, G.[Ge], Zhang, H.[Han], Yu, F.[Fan], Song, Y.H.[Yong-Hong], Zhang, Y.L.[Yuan-Lin], Yuan, H.[Han],
You Ought to Look Around: Precise, Large Span Action Detection,
ICPR21(1574-1581)
IEEE DOI 2105
Location awareness, Fuses, Convolution, Semantics, Feature extraction, Proposals BibRef

He, J.[Jiayu], Li, G.H.[Guo-Hui], Lei, J.[Jun],
Feature Pyramid Hierarchies for Multi-scale Temporal Action Detection,
ICPR21(2158-2165)
IEEE DOI 2105
Image motion analysis, Semantics, Pipelines, Feature extraction, Safety BibRef

Peng, H.[Han], Razi, A.[Abolfazl],
Fully Autonomous UAV-Based Action Recognition System Using Aerial Imagery,
ISVC20(I:276-290).
Springer DOI 2103
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Price, W.[Will], Damen, D.[Dima],
Play Fair: Frame Attributions in Video Models,
ACCV20(V:480-497).
Springer DOI 2103
Explain action models. BibRef

Algamdi, A.M., Sanchez, V., Li, C.T.,
Dronecaps: Recognition of Human Actions in Drone Videos Using Capsule Networks With Binary Volume Comparisons,
ICIP20(3174-3178)
IEEE DOI 2011
Videos, Feature extraction, Drones, Routing, Human Action Recognition 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

Cooray, T.[Thilini], Cheung, N.M.[Ngai-Man], Lu, W.[Wei],
Attention-Based Context Aware Reasoning for Situation Recognition,
CVPR20(4735-4744)
IEEE DOI 2008
Semantics, Visualization, Task analysis, Cognition, Predictive models, Image coding, Knowledge discovery BibRef

Battash, B., Barad, H., Tang, H., Bleiweiss, A.,
Mimic The Raw Domain: Accelerating Action Recognition in the Compressed Domain,
EDLCV20(2926-2934)
IEEE DOI 2008
Task analysis, Data models, Optical computing, Adaptive optics, Optical imaging, Acceleration BibRef

Li, Y., Ji, B., Shi, X., Zhang, J., Kang, B., Wang, L.,
TEA: Temporal Excitation and Aggregation for Action Recognition,
CVPR20(906-915)
IEEE DOI 2008
Videos, Spatiotemporal phenomena, Optical imaging, Feature extraction, Stacking BibRef

Ulutan, O., Rallapalli, S., Srivatsa, M., Torres, C., Manjunath, B.S.,
Actor Conditioned Attention Maps for Video Action Detection,
WACV20(516-525)
IEEE DOI 2006
Feature extraction, Context modeling, Task analysis, Shape, Detectors, Pipelines BibRef

Zhang, J., Felsen, P., Kanazawa, A., Malik, J.,
Predicting 3D Human Dynamics From Video,
ICCV19(7113-7122)
IEEE DOI 2004
Code, Human Motion.
WWW Link. autoregressive processes, image motion analysis, image sequences, solid modelling, video signal processing, Shape BibRef

Roig, C., Sarmiento, M., Varas, D., Masuda, I., Riveiro, J.C., Bou-Balust, E.,
Multi-Modal Pyramid Feature Combination for Human Action Recognition,
MMVAMTC19(3742-3746)
IEEE DOI 2004
feature extraction, gesture recognition, image fusion, image motion analysis, object detection, Feature combination BibRef

Ramanathan, V.[Vignesh], Wang, R.[Rui], Mahajan, D.[Dhruv],
PreDet: Large-scale weakly supervised pre-training for detection,
ICCV21(2845-2855)
IEEE DOI 2203
Training, Location awareness, Analytical models, Computational modeling, Object detection, Noise measurement, BibRef

Ghadiyaram, D.[Deepti], Tran, D.[Du], Mahajan, D.[Dhruv],
Large-Scale Weakly-Supervised Pre-Training for Video Action Recognition,
CVPR19(12038-12047).
IEEE DOI 2002
BibRef

Liu, Z.G.[Zhen-Guang], Wu, S.[Shuang], Jin, S.Y.[Shu-Yuan], Liu, Q.[Qi], Lu, S.J.[Shi-Jian], Zimmermann, R.[Roger], Cheng, L.[Li],
Towards Natural and Accurate Future Motion Prediction of Humans and Animals,
CVPR19(9996-10004).
IEEE DOI 2002
BibRef

Munro, J.[Jonathan], Damen, D.[Dima],
Multi-Modal Domain Adaptation for Fine-Grained Action Recognition,
CVPR20(119-129)
IEEE DOI 2008
BibRef
Earlier: MMVAMTC19(3723-3726)
IEEE DOI 2004
Training, Task analysis, Target recognition, Feature extraction, Adaptation models, Robustness. image fusion, image motion analysis, image recognition, multimodal domain adaptation, Multimodal BibRef

Wray, M., Csurka, G., Larlus, D., Damen, D.[Dima],
Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings,
ICCV19(450-459)
IEEE DOI 2004
learning (artificial intelligence), natural language processing, speech recognition, text analysis, Visualization 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

Shou, Z.[Zheng], Lin, X.D.[Xu-Dong], Kalantidis, Y.[Yannis], Sevilla-Lara, L.[Laura], Rohrbach, M.[Marcus], Chang, S.F.[Shih-Fu], Yan, Z.C.[Zhi-Cheng],
DMC-Net: Generating Discriminative Motion Cues for Fast Compressed Video Action Recognition,
CVPR19(1268-1277).
IEEE DOI 2002
BibRef

Zhao, R.[Rui], Xu, W.[Wanru], Su, H.[Hui], Ji, Q.A.[Qi-Ang],
Bayesian Hierarchical Dynamic Model for Human Action Recognition,
CVPR19(7725-7734).
IEEE DOI 2002
BibRef

Wang, W., Wu, Y., Liu, H., Wang, S., Cheng, J.,
Temporal Action Detection by Joint Identification-Verification,
ICPR18(2026-2031)
IEEE DOI 1812
feature extraction, image classification, image recognition, object detection, video signal processing, action category, Predictive models 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

Ali, A., Taylor, G.W.,
Real-Time End-to-End Action Detection with Two-Stream Networks,
CRV18(31-38)
IEEE DOI 1812
Optical imaging, Task analysis, Real-time systems, Proposals, Optical computing, Integrated optics, Training, Action detection, Video understanding 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

Wang, D.[Dongang], Ouyang, W.L.[Wan-Li], Li, W.[Wen], Xu, D.[Dong],
Dividing and Aggregating Network for Multi-view Action Recognition,
ECCV18(IX: 457-473).
Springer DOI 1810
BibRef

Cortés, X.[Xavier], Conte, D.[Donatello], Cardot, H.[Hubert],
A new bag of visual words encoding method for human action recognition,
ICPR18(2480-2485)
IEEE DOI 1812
BibRef
And:
Bags of Graphs for Human Action Recognition,
SSSPR18(429-438).
Springer DOI 1810
Visualization, Encoding, Videos, Vector quantization, Training, Histograms, Classification algorithms BibRef

Zhong, Y., Zheng, W.,
Unsupervised Learning for Forecasting Action Representations,
ICIP18(1073-1077)
IEEE DOI 1809
Videos, Forecasting, Predictive models, Feature extraction, Training, TV, Context modeling, Unsupervised learning, temporal context, action forecasting BibRef

Liu, D., Wang, Y., Kato, J.,
Evaluation of Triple-Stream Convolutional Networks for Action Recognition,
DICTA17(1-6)
IEEE DOI 1804
image motion analysis, image recognition, image representation, video signal processing, Triple-Stream Convolutional Networks, Videos BibRef