Chen, C.H.[Chang-Hong],
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IVC(55, Part 2), No. 1, 2016, pp. 119-126.
Elsevier DOI
1612
Action recognition
BibRef
Xu, T.T.[Tian-Tian],
Zhu, F.[Fan],
Wong, E.K.[Edward K.],
Fang, Y.[Yi],
Dual many-to-one-encoder-based transfer learning for cross-dataset
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IVC(55, Part 2), No. 1, 2016, pp. 127-137.
Elsevier DOI
1612
Cross-dataset
BibRef
Rahmani, H.[Hossein],
Mahmood, A.[Arif],
Huynh, D.Q.[Du Q.],
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Histogram of Oriented Principal Components for Cross-View Action
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PAMI(38), No. 12, December 2016, pp. 2430-2443.
IEEE DOI
1609
Detectors
BibRef
Rahmani, H.[Hossein],
Mian, A.[Ajmal],
3D Action Recognition from Novel Viewpoints,
CVPR16(1506-1515)
IEEE DOI
1612
BibRef
Earlier:
Learning a non-linear knowledge transfer model for cross-view action
recognition,
CVPR15(2458-2466)
IEEE DOI
1510
BibRef
Rahmani, H.[Hossein],
Mahmood, A.[Arif],
Huynh, D.Q.[Du Q.],
Mian, A.[Ajmal],
Real time action recognition using histograms of depth gradients and
random decision forests,
WACV14(626-633)
IEEE DOI
1406
Feature extraction
BibRef
Brutti, A.[Alessio],
Cavallaro, A.[Andrea],
Online Cross-Modal Adaptation for Audio-Visual Person Identification
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HMS(47), No. 1, February 2017, pp. 40-51.
IEEE DOI
1702
audio-visual systems
BibRef
Brutti, A.[Alessio],
Cavallaro, A.[Andrea],
Unsupervised Cross-Modal Deep-Model Adaptation for Audio-Visual
Re-identification with Wearable Cameras,
CVAVM17(438-445)
IEEE DOI
1802
Adaptation models, Cameras, Feature extraction, Labeling,
Speech recognition, Training, Visualization
BibRef
Rahmani, H.,
Mian, A.,
Shah, M.,
Learning a Deep Model for Human Action Recognition from Novel
Viewpoints,
PAMI(40), No. 3, March 2018, pp. 667-681.
IEEE DOI
1802
Knowledge transfer, Solid modeling,
Training, Trajectory, Videos, Cross-view,
view knowledge transfer
BibRef
Rahmani, H.,
Bennamoun, M.,
Learning Action Recognition Model from Depth and Skeleton Videos,
ICCV17(5833-5842)
IEEE DOI
1802
human computer interaction, image motion analysis,
image representation, image sensors,
Videos
BibRef
Liu, Y.[Yang],
Lu, Z.Y.[Zhao-Yang],
Li, J.[Jing],
Yang, T.[Tao],
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CirSysVideo(29), No. 8, August 2019, pp. 2416-2430.
IEEE DOI
1908
Videos, Dictionaries, Robustness, Machine learning, Sparse matrices,
Noise reduction, Cameras, Action recognition, cross-view,
distribution adaptation
BibRef
Jia, C.,
Ding, Z.,
Kong, Y.,
Fu, Y.,
Semi-Supervised Cross-Modality Action Recognition by Latent Tensor
Transfer Learning,
CirSysVideo(30), No. 9, September 2020, pp. 2801-2814.
IEEE DOI
2009
Correlation, Training, Feature extraction, Target recognition,
Tensors, Testing, Semantics, RGB-D action, cross-modality,
low-rank tensor
BibRef
Zhang, L.L.[Ling-Ling],
Chang, X.J.[Xiao-Jun],
Liu, J.[Jun],
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PR(108), 2020, pp. 107348.
Elsevier DOI
2008
Few-shot learning, Activity recognition, Cross-modal memory
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Lu, M.Q.[Ming-Qi],
Yang, S.Y.[Si-Yuan],
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Liu, J.[Jun],
Cross-Modal Contrastive Pre-Training for Few-Shot Skeleton Action
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CirSysVideo(34), No. 10, October 2024, pp. 9798-9807.
IEEE DOI
2411
Skeleton, Training, Feature extraction, Image recognition,
Task analysis, Metalearning, Computational modeling,
knowledge distillation
BibRef
Chang, X.J.[Xiao-Jun],
Ma, Z.G.[Zhi-Gang],
Yang, Y.[Yi],
Zeng, Z.Q.[Zhi-Qiang],
Hauptmann, A.G.[Alexander G.],
Bi-Level Semantic Representation Analysis for Multimedia Event
Detection,
Cyber(47), No. 5, May 2017, pp. 1180-1197.
IEEE DOI
1704
Detectors
BibRef
Lan, Z.Z.[Zhen-Zhong],
Yang, Y.[Yi],
Ballas, N.[Nicolas],
Yu, S.I.[Shoou-I],
Hauptmann, A.G.[Alexander G.],
Resource Constrained Multimedia Event Detection,
MMMod14(I: 388-399).
Springer DOI
1405
BibRef
Xu, Z.W.[Zhong-Wen],
Yang, Y.[Yi],
Hauptmann, A.G.[Alexander G.],
A discriminative CNN video representation for event detection,
CVPR15(1798-1807)
IEEE DOI
1510
BibRef
Fan, H.,
Chang, X.J.[Xiao-Jun],
Cheng, D.,
Yang, Y.[Yi],
Xu, D.,
Hauptmann, A.G.[Alexander G.],
Complex Event Detection by Identifying Reliable Shots from Untrimmed
Videos,
ICCV17(736-744)
IEEE DOI
1802
feature extraction, image classification,
learning (artificial intelligence), optimisation,
Videos
BibRef
Ballas, N.[Nicolas],
Yang, Y.[Yi],
Lan, Z.Z.[Zhen-Zhong],
Delezoide, B.[Bertrand],
Preteux, F.[Francoise],
Hauptmann, A.G.[Alexander G.],
Space-Time Robust Representation for Action Recognition,
ICCV13(2704-2711)
IEEE DOI
1403
WSVM; action recognition; pooling; saliency; sparse regularization
BibRef
Wang, S.[Sen],
Yang, Y.[Yi],
Ma, Z.G.[Zhi-Gang],
Li, X.[Xue],
Pang, C.Y.[Chao-Yi],
Hauptmann, A.G.[Alexander G.],
Action recognition by exploring data distribution and feature
correlation,
CVPR12(1370-1377).
IEEE DOI
1208
BibRef
Shao, Z.,
Li, Y.,
Zhang, H.,
Learning Representations From Skeletal Self-Similarities for
Cross-View Action Recognition,
CirSysVideo(31), No. 1, January 2021, pp. 160-174.
IEEE DOI
2101
Skeleton, Feature extraction,
Learning systems, Wrapping, Spatiotemporal phenomena,
view-invariant representation
BibRef
Zheng, H.[Hui],
Zhang, X.M.[Xin-Ming],
A Cross View Learning Approach for Skeleton-Based Action Recognition,
CirSysVideo(32), No. 5, May 2022, pp. 3061-3072.
IEEE DOI
2205
Convolution, Joints, Task analysis, Feature extraction, Data models,
Bones, Recurrent neural networks, HAR, fusion, inter-view, multi-scale, skeleton
BibRef
Goyal, G.[Gaurvi],
Noceti, N.[Nicoletta],
Odone, F.[Francesca],
Cross-view action recognition with small-scale datasets,
IVC(120), 2022, pp. 104403.
Elsevier DOI
2204
Cross-view action recognition, Pre-trained deep features,
Transfer learning, Multiview action recognition
BibRef
Goyal, G.[Gaurvi],
Noceti, N.[Nicoletta],
Odone, F.[Francesca],
Single View Learning in Action Recognition,
ICPR21(3690-3697)
IEEE DOI
2105
Training, Deep learning, Pipelines, Data acquisition, Training data,
Knowledge transfer
BibRef
Quan, Z.Z.[Zhen-Zhen],
Chen, Q.S.[Qing-Shan],
Zhang, M.[Moyan],
Hu, W.F.[Wei-Feng],
Zhao, Q.[Qiang],
Hou, J.G.[Jian-Gang],
Li, Y.J.[Yu-Jun],
Liu, Z.[Zhi],
MAWKDN: A Multimodal Fusion Wavelet Knowledge Distillation Approach
Based on Cross-View Attention for Action Recognition,
CirSysVideo(33), No. 10, October 2023, pp. 5734-5749.
IEEE DOI
2310
BibRef
Wang, X.[Xiang],
Zhang, S.W.[Shi-Wei],
Qing, Z.W.[Zhi-Wu],
Lv, Y.L.[Yi-Liang],
Gao, C.X.[Chang-Xin],
Sang, N.[Nong],
Cross-domain few-shot action recognition with unlabeled videos,
CVIU(233), 2023, pp. 103737.
Elsevier DOI
2307
Few-shot action recognition, Cross-domain,
Self-supervised learning, Temporal modeling
BibRef
Wang, X.[Xiao],
Yan, Y.[Yan],
Hu, H.M.[Hai-Miao],
Li, B.[Bo],
Wang, H.Z.[Han-Zi],
Cross-Modal Contrastive Learning Network for Few-Shot Action
Recognition,
IP(33), 2024, pp. 1257-1271.
IEEE DOI
2402
Self-supervised learning, Visualization, Semantics,
Image recognition, Task analysis, Feature extraction,
contrastive learning
BibRef
Wang, X.[Xiao],
Ye, W.R.[Wei-Rong],
Qi, Z.A.[Zhong-Ang],
Wang, G.G.[Guang-Ge],
Wu, J.P.[Jian-Ping],
Shan, Y.[Ying],
Qie, X.H.[Xiao-Hu],
Wang, H.Z.[Han-Zi],
Task-Aware Dual-Representation Network for Few-Shot Action
Recognition,
CirSysVideo(33), No. 10, October 2023, pp. 5932-5946.
IEEE DOI
2310
BibRef
Du, K.W.[Kai-Wen],
Ye, W.R.[Wei-Rong],
Guo, H.Y.[Han-Yu],
Yan, Y.[Yan],
Wang, H.Z.[Han-Zi],
Edge Guided Network With Motion Enhancement for Few-Shot Action
Recognition,
CirSysVideo(35), No. 6, June 2025, pp. 5331-5342.
IEEE DOI
2506
Image edge detection, Data mining, Image classification, Training,
Computational modeling, Transformers, Prototypes, Fuses,
motion enhancement
BibRef
Wang, X.[Xiao],
Lu, Y.[Yang],
Yu, W.C.[Wan-Chuan],
Pang, Y.W.[Yan-Wei],
Wang, H.Z.[Han-Zi],
Few-Shot Action Recognition via Multi-View Representation Learning,
CirSysVideo(34), No. 9, September 2024, pp. 8522-8535.
IEEE DOI
2410
Task analysis, Convolution, Representation learning, Training,
Prototypes, Few-shot learning,
multi-view representation learning
BibRef
Wang, G.G.[Guang-Ge],
Ye, W.R.[Wei-Rong],
Wang, X.[Xiao],
Jin, R.R.[Rong-Rong],
Wang, H.Z.[Han-Zi],
Visual Tempo Contrastive Learning for Few-Shot Action Recognition,
ICIP22(1096-1100)
IEEE DOI
2211
Training, Measurement, Visualization, Image coding,
Image recognition, Dynamics, Semantics, Few-shot learning, contrastive learning
BibRef
Mao, Y.Y.[Yun-Yao],
Deng, J.J.[Jia-Jun],
Zhou, W.G.[Wen-Gang],
Lu, Z.B.[Zhen-Bo],
Ouyang, W.L.[Wan-Li],
Li, H.Q.[Hou-Qiang],
I^2MD: 3D Action Representation Learning with Inter- and Intra-Modal
Mutual Distillation,
IJCV(133), No. 7, July 2025, pp. 4944-4961.
Springer DOI
2506
BibRef
Earlier: A1, A3, A4, A2, A6, Only:
CMD: Self-supervised 3D Action Representation Learning with Cross-Modal
Mutual Distillation,
ECCV22(III:734-752).
Springer DOI
2211
BibRef
Hu, R.T.[Ruo-Tong],
Wang, X.Z.[Xian-Zhi],
Chang, X.J.[Xiao-Jun],
Zhang, Y.L.[Yong-Le],
Hu, Y.Q.[Ye-Qi],
Liu, X.Y.[Xin-Yuan],
Yu, S.[Shusong],
CStrCRL: Cross-View Contrastive Learning Through Gated GCN With
Strong Augmentations for Skeleton Recognition,
CirSysVideo(34), No. 8, August 2024, pp. 6674-6685.
IEEE DOI Code:
WWW Link.
2408
Skeleton, Task analysis, Logic gates, Semantics,
Unsupervised learning, Data models, ST-GGCN
BibRef
Liu, M.Y.[Meng-Yuan],
Liu, H.[Hong],
Guo, T.Y.[Tian-Yu],
Cross-Model Cross-Stream Learning for Self-Supervised Human Action
Recognition,
HMS(54), No. 6, December 2024, pp. 743-752.
IEEE DOI
2412
Skeleton, Feature extraction, Contrastive learning,
Spatiotemporal phenomena, Human-machine systems, Data mining,
skeleton-based action recognition
BibRef
Chen, Y.[Yang],
He, T.[Tian],
Fu, J.F.[Jun-Feng],
Wang, L.[Ling],
Guo, J.C.[Jing-Cai],
Hu, T.[Ting],
Cheng, H.[Hong],
Vision-Language Meets the Skeleton: Progressively Distillation With
Cross-Modal Knowledge for 3D Action Representation Learning,
MultMed(27), 2025, pp. 2293-2303.
IEEE DOI
2505
Skeleton, Noise measurement, Contrastive learning, Training,
Annotations, Joints, Aerospace electronics, Supervised learning,
vision-language
BibRef
Yang, Y.[Yingyuan],
Liang, G.Y.[Guo-Yuan],
Wang, C.[Can],
Wu, X.J.[Xiao-Jun],
Trunk-branch contrastive network with multi-view deformable
aggregation for multi-view action recognition,
PR(169), 2026, pp. 111923.
Elsevier DOI
2509
Action recognition, Multi-view video analytics,
Deformable attention, Contrastive learning
BibRef
Huang, Y.F.[Yi-Fei],
Chen, G.[Guo],
Xu, J.[Jilan],
Zhang, M.F.[Ming-Fang],
Yang, L.J.[Li-Jin],
Pei, B.Q.[Bao-Qi],
Zhang, H.J.[Hong-Jie],
Dong, L.[Lu],
Wang, Y.[Yali],
Wang, L.M.[Li-Min],
Qiao, Y.[Yu],
EgoExoLearn: A Dataset for Bridging Asynchronous Ego- and Exo-centric
View of Procedural Activities in Real World,
CVPR24(22072-22086)
IEEE DOI Code:
WWW Link.
2410
Bridges, Annotations, Laboratories, Focusing, Benchmark testing,
Planning, egocentric video, cross-view, video dataset
BibRef
Kukleva, A.[Anna],
Sener, F.[Fadime],
Remelli, E.[Edoardo],
Tekin, B.[Bugra],
Sauser, E.[Eric],
Schiele, B.[Bernt],
Ma, S.[Shugao],
X-MIC: Cross-Modal Instance Conditioning for Egocentric Action
Generalization,
CVPR24(26354-26363)
IEEE DOI Code:
WWW Link.
2410
Adaptation models, Visualization, Pipelines,
adapters, prompts, generalization, action recognition
BibRef
Zhang, J.H.[Jiang-Hao],
Zhong, X.[Xian],
Liu, W.X.[Wen-Xuan],
Jiang, K.[Kui],
Yang, Z.W.[Zheng-Wei],
Wang, Z.[Zheng],
Implicit Attention-Based Cross-Modal Collaborative Learning for
Action Recognition,
ICIP23(3020-3024)
IEEE DOI
2312
BibRef
Lin, C.C.[Chung-Ching],
Lin, K.[Kevin],
Wang, L.J.[Li-Juan],
Liu, Z.C.[Zi-Cheng],
Li, L.J.[Lin-Jie],
Crossmodal Representation Learning for Zero-shot Action Recognition,
CVPR22(19946-19956)
IEEE DOI
2210
Training, Representation learning, Visualization, Text recognition,
Computational modeling, Semantics, Benchmark testing,
Video analysis and understanding
BibRef
Yang, L.J.[Li-Jin],
Huang, Y.F.[Yi-Fei],
Sugano, Y.[Yusuke],
Sato, Y.[Yoichi],
Interact before Align: Leveraging Cross-Modal Knowledge for Domain
Adaptive Action Recognition,
CVPR22(14702-14712)
IEEE DOI
2210
Adaptation models, Target recognition, Annotations, Semantics,
Benchmark testing, Data models, Video analysis and understanding
BibRef
Li, L.[Linguo],
Wang, M.[Minsi],
Ni, B.B.[Bing-Bing],
Wang, H.[Hang],
Yang, J.C.[Jian-Cheng],
Zhang, W.J.[Wen-Jun],
3D Human Action Representation Learning via Cross-View Consistency
Pursuit,
CVPR21(4739-4748)
IEEE DOI
2111
Codes, Collaborative work
BibRef
Yang, Y.H.[Yu-Huan],
Liu, A.S.[An-Sheng],
Liu, Y.H.[Yu-Hung],
Yeh, T.H.[Tso-Hsin],
Li, Z.J.[Zi-Jun],
Fu, L.C.[Li-Chen],
Cross-View Action Recognition Using View-Invariant Pose Feature Learned
from Synthetic Data with Domain Adaptation,
ACCV18(II:431-446).
Springer DOI
1906
BibRef
Wang, J.[Jiang],
Nie, X.H.[Xiao-Han],
Xia, Y.[Yin],
Wu, Y.[Ying],
Mining discriminative 3D Poselet for cross-view action recognition,
WACV14(634-639)
IEEE DOI
1406
Detectors
BibRef
Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Viewpoint invariant, View Invariant, Human Action Detection, Human Action Recognition .