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Earlier:
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1510
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Feature extraction, Histograms, Kernel, Manifolds, Measurement,
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Estimation, Network architecture, Neural networks, Optical filters,
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Earlier: A2, A1, A3:
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1710
image recognition, image representation,
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Action recognition, Subtensors, Dense trajectories,
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Earlier:
Motion of Oriented Magnitudes Patterns for Human Action Recognition,
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1701
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BibRef
Earlier:
A fast and accurate motion descriptor for human action recognition
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ICPR16(919-924)
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1705
RBG-D cameras, Action recognition, Low computational latency,
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1904
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1906
Action recognition, Hierarchical modeling, Evolution, Tree kernel
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1906
Acceleration computed from Optical Flow for actions descriptions.
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2211
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1912
Human-robot/machine interaction, Deep learning, Human action recognition
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2002
BibRef
Earlier:
Multiple path search for action tube detection in videos,
ICIP17(4232-4236)
IEEE DOI
1803
convolutional neural nets, feature extraction,
image motion analysis, object detection, video signal processing,
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Complexity theory, Message passing, Proposals,
Radio frequency, Search problems, Videos, Action localization.
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Song, S.J.[Si-Jie],
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2002
Modality compensation, multi-modal, action recognition
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Bernardes Vieira, M.[Marcelo],
Moraes Villela, S.[Saulo],
Tacon, H.[Hemerson],
de Lima Chaves, H.[Hugo],
de Almeida Maia, H.[Helena],
Ttito Concha, D.[Darwin],
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Weighted voting of multi-stream convolutional neural networks for
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2106
Convolutional neural networks, Action recognition, Optical flow rhythm
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Elsevier DOI
2109
Motion feature, Bag of features, Dynamic image, Action recognition
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Roy, D.[Debaditya],
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Action Anticipation Using Pairwise Human-Object Interactions and
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IP(30), 2021, pp. 8116-8129.
IEEE DOI
2110
Transformers, Affordances, Visualization, Task analysis,
Predictive models, Convolutional codes, Feature extraction,
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Loh, S.Y.B.[Si-Yuan Brandon],
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Fernando, B.[Basura],
Long-term Action Forecasting Using Multi-headed Attention-based
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ABAW22(2418-2426)
IEEE DOI
2210
Training, Uncertainty, Recurrent neural networks,
Predictive models, Hybrid power systems
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Roy, D.[Debaditya],
Fernando, B.[Basura],
Action anticipation using latent goal learning,
WACV22(808-816)
IEEE DOI
2202
Training, Computational modeling,
Predictive models, Action and Behavior Recognition
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Jayasundara, V.[Vinoj],
Roy, D.[Debaditya],
Fernando, B.[Basura],
FlowCaps: Optical Flow Estimation with Capsule Networks For Action
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WACV21(3408-3417)
IEEE DOI
2106
Solid modeling,
Computational modeling, Estimation, Encoding
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Zhuang, P.Q.[Pei-Qin],
Guo, Y.[Yu],
Yu, Z.P.[Zhi-Peng],
Zhou, L.P.[Lu-Ping],
Bai, L.[Lei],
Liang, D.[Ding],
Wang, Z.Y.[Zhi-Yong],
Wang, Y.[Yali],
Ouyang, W.L.[Wan-Li],
Action Recognition With Motion Diversification and Dynamic Selection,
IP(31), 2022, pp. 4884-4896.
IEEE DOI
2208
Costs, Visualization, Dynamics, Adaptation models,
Feature extraction, Optical flow, Action recognition,
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Huang, G.X.[Guo-Xi],
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BQN: Busy-Quiet Net Enabled by Motion Band-Pass Module for Action
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IP(31), 2022, pp. 4966-4979.
IEEE DOI
2208
Band-pass filters, Redundancy, Optical flow, Convolution,
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Xie, L.X.[Ling-Xi],
Shu, X.B.[Xiang-Bo],
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PAMI(45), No. 8, August 2023, pp. 10317-10330.
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2307
Feature extraction, Videos, Semantics, Predictive models,
Representation learning, Visualization, Training,
human action recognition
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Yang, M.L.[Ming-Lei],
Song, Y.[Yan],
Shu, X.B.[Xiang-Bo],
Tang, J.H.[Jin-Hui],
Temporal Action Localization Based on Temporal Evolution Model and
Multiple Instance Learning,
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Springer DOI
1901
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Li, Y.X.[Yi-Xuan],
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IP(33), 2024, pp. 1740-1752.
IEEE DOI
2403
Action in an image and link through time.
Detectors, Feature extraction, Location awareness,
Predictive models, Task analysis, Transformers, action recognition
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Zhang, Y.Q.[Yu-Qi],
Li, X.[Xiucheng],
Xie, H.[Hao],
Zhuang, W.J.[Wei-Jun],
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Li, Z.J.[Zhi-Jun],
Multi-Label Action Anticipation for Real-World Videos With Scene
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IP(33), 2024, pp. 3242-3255.
IEEE DOI
2405
Standards, Grammar, Videos, Predictive models, Proposals, Genomics, Focusing,
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Discriminative action tubelet detector for weakly-supervised action
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PR(155), 2024, pp. 110704.
Elsevier DOI
2408
Spatiotemporal action detection, Action proposal, Weakly-supervised learning
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Secrets of Event-Based Optical Flow,
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2211
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Wang, L.,
Koniusz, P.,
Huynh, D.,
Hallucinating IDT Descriptors and I3D Optical Flow Features for
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ICCV19(8697-8707)
IEEE DOI
2004
convolutional neural nets, feature extraction,
image colour analysis, image motion analysis, Training
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Han, T.D.[Teng-Da],
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Memory-augmented Dense Predictive Coding for Video Representation
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Springer DOI
2012
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Han, T.D.[Teng-Da],
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Video Representation Learning by Dense Predictive Coding,
HVU19(1483-1492)
IEEE DOI
2004
image motion analysis, image representation,
learning (artificial intelligence), video coding, video
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IEEE DOI
2002
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Liao, Y.[Yiyi],
Güney, F.[Fatma],
Jampani, V.[Varun],
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On the Integration of Optical Flow and Action Recognition,
GCPR18(281-297).
Springer DOI
1905
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Using Phase Instead of Optical Flow for Action Recognition,
OpticalFlow18(VI:678-691).
Springer DOI
1905
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Topological Labelling of Scene using Background/Foreground Separation
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RSL-CV19(652-660)
IEEE DOI
2004
geometry, image segmentation, image sequences,
principal component analysis, stereo image processing, Superpixels
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Event Extraction Using Transportation of Temporal Optical Flow Fields,
OpticalFlow18(VI:692-705).
Springer DOI
1905
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Zhang, W.[Wei],
Cen, J.P.[Jie-Peng],
Zheng, H.C.[Hui-Cheng],
Temporal Inception Architecture for Action Recognition with
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ICPR18(3216-3221)
IEEE DOI
1812
Kernel, Feature extraction, Videos, Streaming media,
Pattern recognition
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Sun, S.,
Kuang, Z.,
Sheng, L.,
Ouyang, W.,
Zhang, W.,
Optical Flow Guided Feature: A Fast and Robust Motion Representation
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CVPR18(1390-1399)
IEEE DOI
1812
Feature extraction, Optical network units, Optical flow,
Dynamics, Network architecture
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Diba, A.[Ali],
Sharma, V.[Vivek],
Van Gool, L.J.[Luc J.],
Stiefelhagen, R.,
DynamoNet: Dynamic Action and Motion Network,
ICCV19(6191-6200)
IEEE DOI
2004
convolutional neural nets, image classification,
image filtering, image motion analysis, image representation,
Convolution
BibRef
Alwassel, H.[Humam],
Heilbron, F.C.[Fabian Caba],
Escorcia, V.[Victor],
Ghanem, B.[Bernard],
Diagnosing Error in Temporal Action Detectors,
ECCV18(III: 264-280).
Springer DOI
1810
BibRef
Lee, M.G.[Myung-Gi],
Lee, S.[Seungeui],
Son, S.J.[Sung-Joon],
Park, G.[Gyutae],
Kwak, N.[Nojun],
Motion Feature Network: Fixed Motion Filter for Action Recognition,
ECCV18(X: 392-408).
Springer DOI
1810
BibRef
Sun, C.[Chen],
Shrivastava, A.[Abhinav],
Vondrick, C.[Carl],
Sukthankar, R.[Rahul],
Murphy, K.[Kevin],
Schmid, C.[Cordelia],
Relational Action Forecasting,
CVPR19(273-283).
IEEE DOI
2002
BibRef
Sun, C.[Chen],
Shrivastava, A.[Abhinav],
Vondrick, C.[Carl],
Murphy, K.[Kevin],
Sukthankar, R.[Rahul],
Schmid, C.[Cordelia],
Actor-Centric Relation Network,
ECCV18(XI: 335-351).
Springer DOI
1810
BibRef
Liu, C.,
Xu, X.,
Zhang, Y.,
Temporal Attention Network for Action Proposal,
ICIP18(2281-2285)
IEEE DOI
1809
Temporal action proposal, temporal attention,
untrimmed video analysis, neural network
BibRef
Kwon, O.C.,
Kim, J.,
Yoo, C.D.,
Action Recognition: First-and Second-Order 3D Feature in
Bi-Directional Attention Network,
ICIP18(3453-3457)
IEEE DOI
1809
Bidirectional control,
Convolutional neural networks, Visualization, Feeds,
spatio-temporal bi-directional LSTM Attention
BibRef
Yu, R.,
Wang, H.,
Davis, L.S.,
ReMotENet: Efficient Relevant Motion Event Detection for Large-Scale
Home Surveillance Videos,
WACV18(1642-1651)
IEEE DOI
1806
image motion analysis, learning (artificial intelligence),
neural nets, object detection, video surveillance, 3D ConvNets,
Videos
BibRef
Ng, J.Y.H.,
Davis, L.S.,
Temporal Difference Networks for Video Action Recognition,
WACV18(1587-1596)
IEEE DOI
1806
feedforward neural nets, image classification,
image motion analysis, image recognition, image representation,
BibRef
Ng, J.Y.H.,
Choi, J.,
Neumann, J.,
Davis, L.S.[Larry S.],
ActionFlowNet: Learning Motion Representation for Action Recognition,
WACV18(1616-1624)
IEEE DOI
1806
image motion analysis, image recognition, image representation,
image sequences, learning (artificial intelligence), neural nets,
Task analysis
BibRef
Zhang, T.Y.[Tian-Yi],
Niu, L.[Li],
Cai, J.F.[Jian-Fei],
Kot, A.C.[Alex C.],
Action proposals using hierarchical clustering of super-trajectories,
VCIP17(1-4)
IEEE DOI
1804
gesture recognition, sport, unsupervised learning,
video signal processing, action localization task,
Trajectory Grouping
BibRef
Fang, H.,
Thiyagalingam, J.,
Bessis, N.,
Edirisinghe, E.,
Fast and reliable human action recognition in video sequences by
sequential analysis,
ICIP17(3973-3977)
IEEE DOI
1803
Feature extraction, Reliability, Sequential analysis,
Streaming media, Task analysis, Training, Video sequences,
sequential probability ratio test(SPRT)
BibRef
Liu, Z.,
Tian, Y.,
Wang, Z.,
Improving human action recognitionby temporal attention,
ICIP17(870-874)
IEEE DOI
1803
Adaptation models, Feature extraction,
Optical imaging, Recurrent neural networks, Training, Videos,
temporal attention
BibRef
Xiao, X.,
Hu, H.,
Wang, W.,
Trajectories-based motion neighborhood feature for human action
recognition,
ICIP17(4147-4151)
IEEE DOI
1803
Handheld computers, Indexes,
Support vector machines, Trajectory,
linear SVM
BibRef
Pu, J.,
Matsui, Y.,
Yang, F.,
Satoh, S.,
Energy based fast event retrieval in video with temporal match kernel,
ICIP17(885-889)
IEEE DOI
1803
Event retrieval, temporal match kernel
BibRef
Hou, R.[Rui],
Chen, C.[Chen],
Shah, M.[Mubarak],
Tube Convolutional Neural Network (T-CNN) for Action Detection in
Videos,
ICCV17(5823-5832)
IEEE DOI
1802
convolution, feature extraction, image classification,
image motion analysis, image recognition,
Videos
BibRef
Kalogeiton, V.[Vicky],
Weinzaepfel, P.[Philippe],
Ferrari, V.[Vittorio],
Schmid, C.[Cordelia],
Action Tubelet Detector for Spatio-Temporal Action Localization,
ICCV17(4415-4423)
IEEE DOI
1802
convolution, feature extraction, image sequences, object detection,
regression analysis, video signal processing, ACT-detector,
Videos
BibRef
Buch, S.,
Escorcia, V.,
Shen, C.,
Ghanem, B.,
Niebles, J.C.,
SST: Single-Stream Temporal Action Proposals,
CVPR17(6373-6382)
IEEE DOI
1711
Computational modeling, Proposals, Training,
Video sequences, Visualization
BibRef
Sigurdsson, G.A.,
Divvala, S.,
Farhadi, A.,
Gupta, A.,
Asynchronous Temporal Fields for Action Recognition,
CVPR17(5650-5659)
IEEE DOI
1711
Cognition, Hidden Markov models, Semantics, Stochastic processes,
Training, Videos
BibRef
Lan, Z.Z.[Zhen-Zhong],
Yu, S.I.[Shoou-I],
Yao, D.Z.[De-Zhong],
Lin, M.[Ming],
Raj, B.[Bhiksha],
Hauptmann, A.G.[Alexander G.],
The Best of Both Worlds: Combining Data-Independent and Data-Driven
Approaches for Action Recognition,
Robust16(1196-1205)
IEEE DOI
1612
Video features.
BibRef
Yuan, J.[Jun],
Ni, B.B.[Bing-Bing],
Yang, X.K.[Xiao-Kang],
Kassim, A.A.[Ashraf A.],
Temporal Action Localization with Pyramid of Score Distribution
Features,
CVPR16(3093-3102)
IEEE DOI
1612
BibRef
Alwassel, H.[Humam],
Heilbron, F.C.[Fabian Caba],
Ghanem, B.[Bernard],
Action Search: Spotting Actions in Videos and Its Application to
Temporal Action Localization,
ECCV18(IX: 253-269).
Springer DOI
1810
BibRef
Heilbron, F.C.[Fabian Caba],
Niebles, J.C.[Juan Carlos],
Ghanem, B.[Bernard],
Fast Temporal Activity Proposals for Efficient Detection of Human
Actions in Untrimmed Videos,
CVPR16(1914-1923)
IEEE DOI
1612
BibRef
Li, Y.W.[Ying-Wei],
Li, Y.[Yi],
Vasconcelos, N.M.[Nuno M.],
RESOUND: Towards Action Recognition Without Representation Bias,
ECCV18(VI: 520-535).
Springer DOI
1810
BibRef
Li, Y.W.[Ying-Wei],
Li, W.X.[Wei-Xin],
Mahadevan, V.[Vijay],
Vasconcelos, N.M.[Nuno M.],
VLAD3: Encoding Dynamics of Deep Features for Action Recognition,
CVPR16(1951-1960)
IEEE DOI
1612
BibRef
de Souza, C.R.[César Roberto],
Gaidon, A.[Adrien],
Vig, E.[Eleonora],
López, A.M.[Antonio Manuel],
Sympathy for the Details: Dense Trajectories and Hybrid Classification
Architectures for Action Recognition,
ECCV16(VII: 697-716).
Springer DOI
1611
BibRef
Wang, L.M.[Li-Min],
Xiong, Y.J.[Yuan-Jun],
Lin, D.[Dahua],
Van Gool, L.J.[Luc J.],
UntrimmedNets for Weakly Supervised Action Recognition and Detection,
CVPR17(6402-6411)
IEEE DOI
1711
Adaptation models, Feature extraction, Motion pictures, Proposals,
Training, Videos, Visualization
BibRef
Wang, L.M.[Li-Min],
Xiong, Y.J.[Yuan-Jun],
Wang, Z.[Zhe],
Qiao, Y.[Yu],
Lin, D.[Dahua],
Tang, X.[Xiaoou],
Van Gool, L.J.[Luc J.],
Temporal Segment Networks:
Towards Good Practices for Deep Action Recognition,
ECCV16(VIII: 20-36).
Springer DOI
1611
BibRef
Kim, T.S.,
Reiter, A.[Austin],
Interpretable 3D Human Action Analysis with Temporal Convolutional
Networks,
MotionRep17(1623-1631)
IEEE DOI
1709
Activity recognition, Computational modeling, Feature extraction,
Skeleton, Solid modeling.
BibRef
Leyva, R.[Roberto],
Sanchez, V.[Victor],
Li, C.T.[Chang-Tsun],
Fast Binary-Based Video Descriptors for Action Recognition,
DICTA16(1-8)
IEEE DOI
1701
BibRef
Earlier:
A fast binary pair-based video descriptor for action recognition,
ICIP16(4185-4189)
IEEE DOI
1610
Detectors.
3D Binary Pair Differences (3DBPD) for video action recognition.
BibRef
Chen, Q.Q.,
Liu, F.,
Li, X.,
Liu, B.D.,
Zhang, Y.J.,
Saliency-context two-stream convnets for action recognition,
ICIP16(3076-3080)
IEEE DOI
1610
Adaptive optics
BibRef
Li, Z.,
Wang, W.,
Li, N.,
Wang, J.,
Tube ConvNets: Better exploiting motion for action recognition,
ICIP16(3056-3060)
IEEE DOI
1610
Clustering algorithms
BibRef
Wu, Z.X.[Zu-Xuan],
Fu, Y.W.[Yan-Wei],
Jiang, Y.G.[Yu-Gang],
Sigal, L.[Leonid],
Harnessing Object and Scene Semantics for Large-Scale Video
Understanding,
CVPR16(3112-3121)
IEEE DOI
1612
BibRef
Jia, C.C.[Cheng-Cheng],
Pang, W.[Wei],
Fu, Y.[Yun],
Mode-Driven Volume Analysis Based on Correlation of Time Series,
VECTaR14(818-833).
Springer DOI
1504
BibRef
Sun, X.[Xin],
Huang, D.[Di],
Wang, Y.H.[Yun-Hong],
Qin, J.[Jie],
Action recognition based on kinematic representation of video data,
ICIP14(1530-1534)
IEEE DOI
1502
Acceleration
BibRef
Liu, M.Y.[Meng-Yuan],
Liu, H.[Hong],
Sun, Q.R.[Qian-Ru],
Action classification by exploring directional co-occurrence of
weighted stips,
ICIP14(1460-1464)
IEEE DOI
1502
Accuracy
BibRef
Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Spatio-Temporal Techniques for Human Action Recognition and Detection .