McKenna, S.J.[Stephen J.],
Jabri, S.[Sumer],
Duric, Z.[Zoran],
Rosenfeld, A.[Azriel],
Wechsler, H.[Harry],
Tracking Groups of People,
CVIU(80), No. 1, October 2000, pp. 42-56.
DOI Link
0010
BibRef
Earlier: A2, A3, A5, A4, Only:
Detection and Location of People in Video Images Using Adaptive Fusion
of Color and Edge Information,
ICPR00(Vol IV: 627-630).
IEEE DOI
0009
BibRef
Earlier: A1, A2, A3, A5, Only:
Tracking Interacting People,
AFGR00(348-353).
IEEE DOI
0003
BibRef
Raja, Y.,
McKenna, S.J.,
Gong, S.,
Tracking and Segmenting People in Varying Lighting Conditions Using
Colour,
AFGR98(228-233).
IEEE DOI
BibRef
9800
Oliver, N.M.[Nuria M.],
Rosario, B.[Barbara],
Pentland, A.P.[Alex P.],
A Bayesian Computer Vision System for Modeling Human Interactions,
PAMI(22), No. 8, August 2000, pp. 831-843.
IEEE DOI
0010
BibRef
Earlier:
CVS99(255 ff.).
Springer DOI
0209
BibRef
And:
DARPA98(293-297).
BibRef
And:
Vismod--459, March 1998.
PS File. Stat-based learning to model interactions. CHMM model is most effective.
Synthetic model for learning.
BibRef
Dong, W.,
Lepri, B.,
Pianesi, F.,
Pentland, A.,
Modeling Functional Roles Dynamics in Small Group Interactions,
MultMed(15), No. 1, January 2013, pp. 83-95.
IEEE DOI
1212
BibRef
Oliver, N.M.[Nuria M.],
Towards Perceptual Intelligence:
Statistical Modeling of Human Individual and Interactive Behaviors,
Ph.D.Thesis, MIT, Media Lab, 2000.
BibRef
0001
Sanchez-Cortes, D.,
Aran, O.,
Mast, M.S.,
Gatica-Perez, D.[Daniel],
A Nonverbal Behavior Approach to Identify Emergent Leaders in Small
Groups,
MultMed(14), No. 3, 2012, pp. 816-832.
IEEE DOI
1202
BibRef
Chittaranjan, G.[Gokul],
Aran, O.[Oya],
Gatica-Perez, D.[Daniel],
Exploiting observers' judgements for nonverbal group interaction
analysis,
FG11(734-739).
IEEE DOI
1103
BibRef
Hung, H.[Hayley],
Huang, Y.[Yan],
Yeo, C.H.[Chuo-Hao],
Gatica-Perez, D.[Daniel],
Associating audio-visual activity cues in a dominance estimation
framework,
CVPR4HB08(1-6).
IEEE DOI
0806
BibRef
Zhang, W.D.[Wei-Dong],
Chen, F.[Feng],
Xu, W.L.[Wen-Li],
Du, Y.T.[You-Tian],
Hierarchical group process representation in multi-agent activity
recognition,
SP:IC(23), No. 10, November 2008, pp. 739-753,.
Elsevier DOI
0804
Multi-agent activity recognition; Dynamic Bayesian network;
Multi-channel setting; Hierarchical representation
BibRef
Du, Y.T.[You-Tian],
Chen, F.[Feng],
Xu, W.L.[Wen-Li],
Li, Y.B.[Yong-Bin],
Recognizing Interaction Activities using Dynamic Bayesian Network,
ICPR06(I: 618-621).
IEEE DOI
0609
BibRef
Zhang, W.D.[Wei-Dong],
Chen, F.[Feng],
Xu, W.L.[Wen-Li],
Cao, Z.S.[Zi-Sheng],
Decomposition in Hidden Markov Models for Activity Recognition,
MCAM07(232-241).
Springer DOI
0706
BibRef
Gatica-Perez, D.[Daniel],
Automatic nonverbal analysis of social interaction in small groups:
A review,
IVC(27), No. 12, November 2009, pp. 1775-1787,.
Elsevier DOI
0910
Social interaction analysis; Small group conversations; Nonverbal behavior
See also Automatic Analysis of Multimodal Group Actions in Meetings.
BibRef
Hung, H.[Hayley],
Gatica-Perez, D.[Daniel],
Estimating Cohesion in Small Groups Using Audio-Visual Nonverbal
Behavior,
MultMed(12), No. 6, 2010, pp. 563-575.
IEEE DOI
1003
BibRef
Earlier:
Identifying dominant people in meetings from audio-visual sensors,
FG08(1-6).
IEEE DOI
0809
A-V group meeting data.
BibRef
Gatica-Perez, D.,
Lathoud, G.,
McCowan, L.,
Odobez, J.M.,
Moore, D.,
Audio-visual speaker tracking with importance particle filters,
ICIP03(III: 25-28).
IEEE DOI
0312
See also Automatic Analysis of Multimodal Group Actions in Meetings.
BibRef
Odobez, J.M.[Jean-Marc],
Gatica-Perez, D.[Daniel],
Ba, S.O.[Sileye O.],
Embedding Motion in Model-Based Stochastic Tracking,
IP(15), No. 11, November 2006, pp. 3514-3530.
IEEE DOI
0610
BibRef
Earlier: A1, A2 only:
ICPR04(II: 815-818).
IEEE DOI
0409
BibRef
And: A1, A3, A2:
An implicit motion likelihood for tracking with particle filters,
BMVC03(xx-yy).
HTML Version.
0409
BibRef
Smith, K.[Kevin],
Carleton, A.[Alan],
Lepetit, V.[Vincent],
General constraints for batch Multiple-Target Tracking applied to
large-scale videomicroscopy,
CVPR08(1-8).
IEEE DOI
0806
BibRef
Smith, K.[Kevin],
Gatica-Perez, D.[Daniel],
Odobez, J.M.[Jean-Marc],
Ba, S.O.[Sileye O.],
Evaluating Multi-Object Tracking,
EEMCV05(III: 36-36).
IEEE DOI
0507
BibRef
And: A1, A2, A3, Only:
Using Particles to Track Varying Numbers of Interacting People,
CVPR05(I: 962-969).
IEEE DOI
0507
BibRef
Jayagopi, D.B.,
Gatica-Perez, D.,
Mining Group Nonverbal Conversational Patterns Using Probabilistic
Topic Models,
MultMed(12), No. 8, 2010, pp. 790-802.
IEEE DOI
1011
Group behavior, for meetings.
BibRef
Xiang, T.[Tao],
Gong, S.G.[Shao-Gang],
Beyond Tracking: Modelling Activity and Understanding Behaviour,
IJCV(67), No. 1, April 2006, pp. 21-51.
Springer DOI
0604
BibRef
Earlier:
Relevance learning for spectral clustering with applications on image
segmentation and video behaviour profiling,
AVSBS05(28-33).
IEEE DOI
0602
BibRef
And:
Video Behaviour Profiling and Abnormality Detection without Manual
Labelling,
ICCV05(II: 1238-1245).
IEEE DOI
0510
BibRef
Earlier:
Outdoor Activity Recognition using Multi-Linked Temporal Processes,
BMVC03(xx-yy).
HTML Version.
0409
BibRef
Earlier: A2, A1:
Recognition of group activities using dynamic probabilistic networks,
ICCV03(742-749).
IEEE DOI
0311
See also Optimising dynamic graphical models for video content analysis.
BibRef
Xiang, T.[Tao],
Gong, S.G.[Shao-Gang],
Activity based surveillance video content modelling,
PR(41), No. 7, July 2008, pp. 2309-2326.
Elsevier DOI
0804
BibRef
Earlier:
Discovering Bayesian causality among visual events in a complex outdoor
scene,
AVSBS03(177-182).
IEEE DOI
0310
Video content analysis; Activity recognition; Surveillance video segmentation;
Dynamic Bayesian networks; Dynamic scene modelling; Unusual activity detection
BibRef
Sherrah, J.[Jamie],
Gong, S.G.[Shao-Gang],
Howell, A.J.[A. Jonathan],
Buxton, H.[Hilary],
Interpretation of Group Behaviour in Visually Mediated Interaction,
ICPR00(Vol I: 266-269).
IEEE DOI
0009
BibRef
Sherrah, J.[Jamie],
Gong, S.G.[Shao-Gang],
VIGOUR: A System for Tracking and Recognition of Multiple People and
Their Activities,
ICPR00(Vol I: 179-182).
IEEE DOI
0009
BibRef
Wang, Y.D.[Ya-Dong],
Wu, J.K.[Jian-Kang],
Kassim, A.A.[Ashraf A.],
Huang, W.M.[Wei-Min],
Data-Driven Probability Hypothesis Density Filter for Visual Tracking,
CirSysVideo(18), No. 8, August 2008, pp. 1085-1095.
IEEE DOI
0809
BibRef
Earlier:
Tracking a Variable Number of Human Groups in Video Using Probability
Hypothesis Density,
ICPR06(III: 1127-1130).
IEEE DOI
0609
BibRef
Ni, B.B.[Bing-Bing],
Yan, S.C.[Shui-Cheng],
Kassim, A.A.[Ashraf A.],
Recognizing human group activities with localized causalities,
CVPR09(1470-1477).
IEEE DOI
0906
BibRef
Ryoo, M.S.,
Aggarwal, J.K.,
Semantic Representation and Recognition of Continued and Recursive
Human Activities,
IJCV(82), No. 1, April 2009, pp. xx-yy.
Springer DOI
0902
BibRef
Earlier:
Hierarchical Recognition of Human Activities Interacting with Objects,
SLAM07(1-8).
IEEE DOI
0706
BibRef
Earlier:
Semantic Understanding of Continued and Recursive Human Activities,
ICPR06(I: 379-378).
IEEE DOI
0609
BibRef
And:
Recognition of Composite Human Activities through Context-Free Grammar
Based Representation,
CVPR06(II: 1709-1718).
IEEE DOI
0606
BibRef
Ryoo, M.S.,
Grauman, K.[Kristen],
Aggarwal, J.K.,
A task-driven intelligent workspace system to provide guidance feedback,
CVIU(114), No. 5, May 2010, pp. 520-534.
Elsevier DOI
1004
Intelligent environments; Intelligent workspaces; Feedback generation;
Guidance feedback messages; Activity recognition; Event analysis
BibRef
Ryoo, M.S.,
Aggarwal, J.K.,
Stochastic Representation and Recognition of High-Level Group
Activities,
IJCV(93), No. 2, June 2011, pp. 183-200.
WWW Link.
1104
BibRef
Earlier:
Spatio-temporal relationship match:
Video structure comparison for recognition of complex human activities,
ICCV09(1593-1600).
IEEE DOI
0909
BibRef
Earlier:
Stochastic representation and recognition of high-level group activities:
Describing structural uncertainties in human activities,
SIG09(11-11).
IEEE DOI
0906
BibRef
Earlier:
Recognition of High-level Group Activities Based on Activities of
Individual Members,
Motion08(1-8).
IEEE DOI
0801
BibRef
And:
Human activities: Handling uncertainties using fuzzy time intervals,
ICPR08(1-5).
IEEE DOI
0812
BibRef
And:
Observe-and-explain:
A new approach for multiple hypotheses tracking of humans and objects,
CVPR08(1-8).
IEEE DOI
0806
BibRef
Lin, W.,
Sun, M.T.,
Poovendran, R.,
Zhang, Z.,
Group Event Detection With a Varying Number of Group Members for Video
Surveillance,
CirSysVideo(20), No. 8, August 2010, pp. 1057-1067.
IEEE DOI
1008
See also Activity Recognition Using a Combination of Category Components and Local Models for Video Surveillance.
BibRef
Lan, T.[Tian],
Wang, Y.[Yang],
Yang, W.L.[Wei-Long],
Robinovitch, S.N.[Stephen N.],
Mori, G.[Greg],
Discriminative Latent Models for Recognizing Contextual Group
Activities,
PAMI(34), No. 8, August 2012, pp. 1549-1562.
IEEE DOI
1206
Focus on the group. Group-person interaction and person-person.
See also Human Action Recognition by Semilatent Topic Models.
BibRef
Burkert, F.[Florian],
Bamler, R.[Richard],
Graph-Based Analysis of Pedestrian Interactions and Events Using Hidden
Markov Models,
PFG(2012), No. 6, 2012, pp. 701-710.
WWW Link.
1302
BibRef
Burkert, F.[Florian],
Butenuth, M.[Matthias],
Complex Event Detection In Pedestrian Groups From UAVs,
AnnalsPRS(I-3), No. 2012, pp. 335-340.
DOI Link
1209
BibRef
And:
Event Detection Based on a Pedestrian Interaction Graph Using Hidden
Markov Models,
PIA11(271-283).
Springer DOI
1110
BibRef
Noceti, N.[Nicoletta],
Odone, F.[Francesca],
Humans in groups: The importance of contextual information for
understanding collective activities,
PR(47), No. 11, 2014, pp. 3535-3551.
Elsevier DOI
1407
Collective activity recognition
BibRef
Li, R.N.[Ruo-Nan],
Chellappa, R.[Rama],
Zhou, S.H.K.[Shao-Hua Kevin],
Recognizing Interactive Group Activities Using Temporal Interaction
Matrices and Their Riemannian Statistics,
IJCV(101), No. 2, January 2013, pp. 305-328.
WWW Link.
1302
multi-subject activities.
BibRef
Zha, Z.J.,
Zhang, H.,
Wang, M.,
Luan, H.,
Chua, T.S.,
Detecting Group Activities With Multi-Camera Context,
CirSysVideo(23), No. 5, May 2013, pp. 856-869.
IEEE DOI
1305
BibRef
Lin, W.Y.[Wei-Yao],
Chu, H.[Hang],
Wu, J.X.[Jian-Xin],
Sheng, B.[Bin],
Chen, Z.Z.[Zhen-Zhong],
A Heat-Map-Based Algorithm for Recognizing Group Activities in Videos,
CirSysVideo(23), No. 11, 2013, pp. 1980-1992.
IEEE DOI
1312
feature extraction
BibRef
Avci, U.,
Aran, O.,
Predicting the Performance in Decision-Making Tasks:
From Individual Cues to Group Interaction,
MultMed(18), No. 4, April 2016, pp. 643-658.
IEEE DOI
1604
Computational modeling
BibRef
Wu, J.X.[Jian-Xin],
Zhang, Y.[Yu],
Lin, W.Y.[Wei-Yao],
Good Practices for Learning to Recognize Actions Using FV and VLAD,
Cyber(46), No. 12, December 2016, pp. 2978-2990.
IEEE DOI
1612
BibRef
Earlier:
Towards Good Practices for Action Video Encoding,
CVPR14(2577-2584)
IEEE DOI
1409
Accuracy
BibRef
Li, R.N.[Ruo-Nan],
Turaga, P.K.[Pavan K.],
Srivastava, A.[Anuj],
Chellappa, R.[Rama],
Differential geometric representations and algorithms for some
pattern recognition and computer vision problems,
PRL(43), No. 1, 2014, pp. 3-16.
Elsevier DOI
1404
Manifold
BibRef
Li, R.N.[Ruo-Nan],
Chellappa, R.[Rama],
Zhou, S.H.K.[Shao-Hua Kevin],
Learning multi-modal densities on Discriminative Temporal Interaction
Manifold for group activity recognition,
CVPR09(2450-2457).
IEEE DOI
0906
BibRef
Wang, C.,
Cao, L.,
Chi, C.,
Formalization and Verification of Group Behavior Interactions,
SMCS(45), No. 8, August 2015, pp. 1109-1124.
IEEE DOI
1506
Analytical models
BibRef
Chen, C.H.[Chang-Hong],
Dou, H.[Hehe],
Gan, Z.L.[Zong-Liang],
Collective Activity Recognition by Attribute-Based Spatio-Temporal
Descriptor,
IEICE(E98-D), No. 10, October 2015, pp. 1875-1878.
WWW Link.
1511
BibRef
Amer, M.R.[Mohamed R.],
Todorovic, S.[Sinisa],
Sum Product Networks for Activity Recognition,
PAMI(38), No. 4, April 2016, pp. 800-813.
IEEE DOI
1603
BibRef
Earlier:
Sum-product networks for modeling activities with stochastic structure,
CVPR12(1314-1321).
IEEE DOI
1208
BibRef
Earlier:
A chains model for localizing participants of group activities in
videos,
ICCV11(786-793).
IEEE DOI
1201
Computational modeling
BibRef
Amer, M.R.[Mohamed R.],
Todorovic, S.[Sinisa],
Fern, A.[Alan],
Zhu, S.C.[Song-Chun],
Monte Carlo Tree Search for Scheduling Activity Recognition,
ICCV13(1353-1360)
IEEE DOI
1403
Activity Recogition
BibRef
Amer, M.R.[Mohamed R.],
Xie, D.[Dan],
Zhao, M.T.[Ming-Tian],
Todorovic, S.[Sinisa],
Zhu, S.C.[Song-Chun],
Cost-Sensitive Top-Down/Bottom-Up Inference for Multiscale Activity
Recognition,
ECCV12(IV: 187-200).
Springer DOI
1210
BibRef
Brendel, W.[William],
Amer, M.R.[Mohamed R.],
Todorovic, S.[Sinisa],
Multiobject tracking as maximum weight independent set,
CVPR11(1273-1280).
IEEE DOI
1106
BibRef
Earlier: A1, A3, Only:
Video object segmentation by tracking regions,
ICCV09(833-840).
IEEE DOI
0909
BibRef
Iqbal, T.,
Riek, L.D.,
A Method for Automatic Detection of Psychomotor Entrainment,
AffCom(7), No. 1, January 2016, pp. 3-16.
IEEE DOI
1603
Atmospheric measurements
BibRef
Sun, L.[Lei],
Ai, H.Z.[Hai-Zhou],
Lao, S.H.[Shi-Hong],
Localizing activity groups in videos,
CVIU(144), No. 1, 2016, pp. 144-154.
Elsevier DOI
1604
Activity recognition
BibRef
Zhao, F.[Fang],
Huang, Y.Z.[Yong-Zhen],
Wang, L.[Liang],
Xiang, T.[Tao],
Tan, T.N.[Tie-Niu],
Learning Relevance Restricted Boltzmann Machine for Unstructured Group
Activity and Event Understanding,
IJCV(119), No. 3, September 2016, pp. 329-345.
Springer DOI
1608
BibRef
Gebru, I.D.,
Alameda-Pineda, X.,
Forbes, F.,
Horaud, R.[Radu],
EM Algorithms for Weighted-Data Clustering with Application to
Audio-Visual Scene Analysis,
PAMI(38), No. 12, December 2016, pp. 2402-2415.
IEEE DOI
1609
Algorithm design and analysis
BibRef
Gebru, I.D.,
Ba, S.O.,
Li, X.,
Horaud, R.,
Audio-Visual Speaker Diarization Based on Spatiotemporal Bayesian
Fusion,
PAMI(40), No. 5, May 2018, pp. 1086-1099.
IEEE DOI
1804
Cameras, Face, Feature extraction,
Mel frequency cepstral coefficient, Microphones, Speech,
sound source localization
BibRef
Gebru, I.D.,
Ba, S.O.,
Evangelidis, G.[Georgios],
Horaud, R.[Radu],
Tracking the Active Speaker Based on a Joint Audio-Visual Observation
Model,
p
3DVS15(702-708)
IEEE DOI
1602
Acoustics
BibRef
Lathuilière, S.[Stéphane],
Evangelidis, G.[Georgios],
Horaud, R.[Radu],
Recognition of Group Activities in Videos Based on Single-and
Two-Person Descriptors,
WACV17(217-225)
IEEE DOI
1609
Computational modeling, Context, Feature extraction, Optimization,
Support vector machines, Training, Videos
BibRef
Kiliç, V.[Volkan],
Barnard, M.[Mark],
Wang, W.W.[Wen-Wu],
Hilton, A.[Adrian],
Kittler, J.V.[Josef V.],
Mean-Shift and Sparse Sampling-Based SMC-PHD Filtering for Audio
Informed Visual Speaker Tracking,
MultMed(18), No. 12, December 2016, pp. 2417-2431.
IEEE DOI
1612
Bayes methods
BibRef
Gao, C.,
Liu, J.,
Network-Based Modeling for Characterizing Human Collective Behaviors
During Extreme Events,
SMCS(47), No. 1, January 2017, pp. 171-183.
IEEE DOI
1612
Feedback loop
BibRef
García-Martín, Á.[Álvaro],
Sánchez-Matilla, R.[Ricardo],
Martínez, J.M.[José M.],
Hierarchical detection of persons in groups,
SIViP(11), No. 7, October 2017, pp. 1181-1188.
Springer DOI
1708
BibRef
Jang, H.,
Choe, S.P.,
Gunkel, S.N.B.,
Kang, S.,
Song, J.,
A System to Analyze Group Socializing Behaviors in Social Parties,
HMS(47), No. 6, December 2017, pp. 801-813.
IEEE DOI
1712
Behavioral sciences, Context awareness, Man-machine systems,
Monitoring, Noise measurement, Real-time systems, Sensors,
ubiquitous computing
BibRef
Tang, M.F.[Meng-Fan],
Nie, F.P.[Fei-Ping],
Pongpaichet, S.[Siripen],
Jain, R.C.[Ramesh C.],
Semi-supervised learning on large-scale geotagged photos for
situation recognition,
JVCIR(48), No. 1, 2017, pp. 310-316.
Elsevier DOI
1708
Evolving situations
BibRef
Kim, P.S.[Pil-Soo],
Lee, D.G.[Dong-Gyu],
Lee, S.W.[Seong-Whan],
Discriminative context learning with gated recurrent unit for group
activity recognition,
PR(76), No. 1, 2018, pp. 149-161.
Elsevier DOI
1801
Group activity recognition
BibRef
Kim, Y.J.[Young-Ji],
Cho, N.G.[Nam-Gyu],
Lee, S.W.[Seong-Whan],
Group Activity Recognition with Group Interaction Zone,
ICPR14(3517-3521)
IEEE DOI
1412
Clustering algorithms
BibRef
Xie, D.[Dan],
Shu, T.[Tianmin],
Todorovic, S.[Sinisa],
Zhu, S.C.[Song-Chun],
Learning and Inferring 'Dark Matter: and Predicting Human Intents and
Trajectories in Videos,
PAMI(40), No. 7, July 2018, pp. 1639-1652.
IEEE DOI
1806
Cognition, Force, Surveillance, Training, Trajectory,
Videos, Scene understanding, functional objects, intents modeling,
video analysis
BibRef
Shu, T.[Tianmin],
Xie, D.[Dan],
Rothrock, B.[Brandon],
Todorovic, S.[Sinisa],
Zhu, S.C.[Song-Chun],
Joint inference of groups, events and human roles in aerial videos,
CVPR15(4576-4584)
IEEE DOI
1510
BibRef
Bensebaa, A.[Amina],
Larabi, S.[Slimane],
Direction estimation of moving pedestrian groups for intelligent
vehicles,
VC(34), No. 6-8, June 2018, pp. 1109-1118.
WWW Link.
1806
BibRef
Polhill, J.G.[J. Gareth],
Ge, J.Q.[Jia-Qi],
Hare, M.P.[Matthew P.],
Matthews, K.B.[Keith B.],
Gimona, A.[Alessandro],
Salt, D.[Douglas],
Yeluripati, J.[Jagadeesh],
Crossing the chasm: a 'tube-map' for agent-based social simulation of
policy scenarios in spatially-distributed systems,
GeoInfo(23), No. 2, Apriul 2019, pp. 169-199.
Springer DOI
1906
Actions of individuals and groups and how they affect the whole.
BibRef
Mou, W.X.[Wen-Xuan],
Tzelepis, C.[Christos],
Mezaris, V.[Vasileios],
Gunes, H.[Hatice],
Patras, I.[Ioannis],
A deep generic to specific recognition model for group membership
analysis using non-verbal cues,
IVC(81), 2019, pp. 42-50.
Elsevier DOI
1902
BibRef
Earlier:
Generic to Specific Recognition Models for Membership Analysis in
Group Videos,
FG17(512-517)
IEEE DOI
1707
Non-verbal behavior analysis, Group membership,
Automatic group analysis, Deep learning.
Data models, Feature extraction, Motion pictures, Optimization,
Support vector machines, Training, Videos
BibRef
Lu, L.H.[Li-Hua],
Di, H.J.[Hui-Jun],
Lu, Y.[Yao],
Zhang, L.[Lin],
Wang, S.Z.[Shun-Zhou],
Spatio-temporal attention mechanisms based model for collective
activity recognition,
SP:IC(74), 2019, pp. 162-174.
Elsevier DOI
1904
Multi-person activity recognition, Spatio-temporal model,
Attention mechanisms, Multi-modal data, Gated Recurrent Units (GRUs) network
BibRef
Yao, R.H.[Rui-Hong],
Wang, F.[Fei],
Chen, S.H.[Shu-Hui],
Zhao, S.[Shuang],
GroupSeeker: An Applicable Framework for Travel Companion Discovery
from Vast Trajectory Data,
IJGI(9), No. 6, 2020, pp. xx-yy.
DOI Link
2006
BibRef
Lu, L.H.[Li-Hua],
Lu, Y.[Yao],
Yu, R.Z.[Rui-Zhe],
Di, H.J.[Hui-Jun],
Zhang, L.[Lin],
Wang, S.Z.[Shun-Zhou],
GAIM: Graph Attention Interaction Model for Collective Activity
Recognition,
MultMed(22), No. 2, February 2020, pp. 524-539.
IEEE DOI
2001
Activity recognition, Recurrent neural networks, Task analysis,
Graphical models, Convolutional neural networks,
Collective Activity Recognition
BibRef
Tang, Y.,
Lu, J.,
Wang, Z.,
Yang, M.,
Zhou, J.,
Learning Semantics-Preserving Attention and Contextual Interaction
for Group Activity Recognition,
IP(28), No. 10, October 2019, pp. 4997-5012.
IEEE DOI
1909
Activity recognition, Semantics, Task analysis, Feature extraction,
Knowledge engineering, Computational modeling,
Teacher-Student networks
BibRef
Zhang, P.,
Tang, Y.,
Hu, J.,
Zheng, W.,
Fast Collective Activity Recognition Under Weak Supervision,
IP(29), No. 1, 2020, pp. 29-43.
IEEE DOI
1910
data mining, image recognition,
inference mechanisms, learning (artificial intelligence),
joint learning
BibRef
Qi, M.S.[Meng-Shi],
Wang, Y.H.[Yun-Hong],
Qin, J.[Jie],
Li, A.[Annan],
Luo, J.B.[Jie-Bo],
Van Gool, L.J.[Luc J.],
stagNet: An Attentive Semantic RNN for Group Activity and Individual
Action Recognition,
CirSysVideo(30), No. 2, February 2020, pp. 549-565.
IEEE DOI
2002
BibRef
Earlier: A1, A3, A4, A2, A5, A6:
stagNet: An Attentive Semantic RNN for Group Activity Recognition,
ECCV18(X: 104-120).
Springer DOI
1810
Semantics, Hidden Markov models, Activity recognition,
Recurrent neural networks, Task analysis, Adaptation models,
Scene Understanding
BibRef
Kong, Y.Q.[Yong-Qiang],
Wang, Y.H.[Yun-Hong],
Li, A.[Annan],
Spatiotemporal Saliency Representation Learning for Video Action
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MultMed(24), 2022, pp. 1515-1528.
IEEE DOI
2204
Object detection, Spatiotemporal phenomena,
Task analysis, Solid modeling, spatiotemporal CNNs
BibRef
Wang, L.,
Zhang, Y.,
Zhao, X.,
Liu, H.,
Zhang, K.,
Irregular Travel Groups Detection Based on Cascade Clustering in
Urban Subway,
ITS(21), No. 5, May 2020, pp. 2216-2225.
IEEE DOI
2005
Public transportation, Clustering algorithms, Smart cards,
Feature extraction, Frequency measurement, Correlation,
passenger similarity
BibRef
Sendo, K.[Kohei],
Ukita, N.[Norimichi],
Heatmapping of Group People Involved in the Group Activity,
IEICE(E103-D), No. 6, June 2020, pp. 1209-1216.
WWW Link.
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Cabrera-Quiros, L.,
Demetriou, A.,
Gedik, E.,
van der Meij, L.,
Hung, H.,
The MatchNMingle Dataset: A Novel Multi-Sensor Resource for the
Analysis of Social Interactions and Group Dynamics In-the-Wild During
Free-Standing Conversations and Speed Dates,
AffCom(12), No. 1, January 2021, pp. 113-130.
IEEE DOI
2103
Cameras, Manuals, Acceleration, Crowdsourcing, Task analysis, Sensors,
Computers, Multimodal dataset, speed-dates, mingle, f-formation,
personality traits
BibRef
Zhang, L.,
Hung, H.,
On Social Involvement in Mingling Scenarios: Detecting Associates of
F-Formations in Still Images,
AffCom(12), No. 1, January 2021, pp. 165-176.
IEEE DOI
2103
Task analysis, Semantics, Psychology, Feature extraction, Labeling,
Surveillance, Visualization, F-formations detection,
social group detection
BibRef
Xu, J.W.[Jing-Wei],
Ni, B.B.[Bing-Bing],
Yang, X.K.[Xiao-Kang],
Progressive Multi-granularity Analysis for Video Prediction,
IJCV(129), No. 3, March 2021, pp. 601-618.
Springer DOI
2103
BibRef
Yao, T.P.[Tai-Ping],
Wang, M.[Minsi],
Ni, B.B.[Bing-Bing],
Wei, H.W.[Hua-Wei],
Yang, X.K.[Xiao-Kang],
Multiple Granularity Group Interaction Prediction,
CVPR18(2246-2254)
IEEE DOI
1812
Trajectory, Skeleton, Generators, Predictive models, Task analysis,
Feature extraction, Activity recognition
BibRef
Chen, Y.Y.[Yan-Yu],
Zheng, W.Z.[Wen-Zhe],
Li, W.B.[Wen-Bo],
Huang, Y.M.[Yi-Miao],
Large group activity security risk assessment and risk early warning
based on random forest algorithm,
PRL(144), 2021, pp. 1-5.
Elsevier DOI
2103
Random forest algorithm, Large-scale group activities,
Security risk assessment, Risk warning
BibRef
Vo, M.[Minh],
Yumer, E.[Ersin],
Sunkavalli, K.[Kalyan],
Hadap, S.I.[Sun-Il],
Sheikh, Y.[Yaser],
Narasimhan, S.G.[Srinivasa G.],
Self-Supervised Multi-View Person Association and its Applications,
PAMI(43), No. 8, August 2021, pp. 2794-2808.
IEEE DOI
2107
Multiple cameras, multiple people.
Cameras, Skeleton, Target tracking,
Streaming media, Reliability, Descriptor adaptation, multi-angle video
BibRef
Mao, W.[Wei],
Liu, M.M.[Miao-Miao],
Salzmann, M.[Mathieu],
Li, H.D.[Hong-Dong],
Multi-level Motion Attention for Human Motion Prediction,
IJCV(129), No. 9, September 2021, pp. 2513-2535.
Springer DOI
2108
BibRef
Earlier: A1, A2, A3, Only:
History Repeats Itself: Human Motion Prediction via Motion Attention,
ECCV20(XIV:474-489).
Springer DOI
2011
BibRef
Pramono, R.R.A.[Rizard Renanda Adhi],
Fang, W.H.[Wen-Hsien],
Chen, Y.T.[Yie-Tarng],
Relational Reasoning for Group Activity Recognition via
Self-Attention Augmented Conditional Random Field,
IP(30), 2021, pp. 8184-8199.
IEEE DOI
2110
BibRef
Earlier: A1, A3, A2:
Empowering Relational Network by Self-attention Augmented Conditional
Random Fields for Group Activity Recognition,
ECCV20(I:71-90).
Springer DOI
2011
Feature extraction, Activity recognition, Videos, Semantics,
Transformers, Context modeling,
bidirectional universal transformer encoder
BibRef
Perez, M.[Mauricio],
Liu, J.[Jun],
Kot, A.C.[Alex C.],
Skeleton-based relational reasoning for group activity analysis,
PR(122), 2022, pp. 108360.
Elsevier DOI
2112
Group activity recognition, Skeleton information,
Relational network, Attention mechanisms
BibRef
Böck, R.[Ronald],
Affects in Groups: A review on automated affect processing and
estimation in groups,
SPMag(38), No. 6, November 2021, pp. 74-83.
IEEE DOI
2112
Affective computing, Social sciences, Estimation, Tutorials,
SIgnal analysis, Benchmark testing
BibRef
Tang, J.H.[Jin-Hui],
Shu, X.B.[Xiang-Bo],
Yan, R.[Rui],
Zhang, L.Y.[Li-Yan],
Coherence Constrained Graph LSTM for Group Activity Recognition,
PAMI(44), No. 2, February 2022, pp. 636-647.
IEEE DOI
2201
Coherence, Activity recognition, Logic gates, Motion measurement,
Time measurement, Recurrent neural networks, Games,
deep learning
BibRef
Du, B.[Bo],
Zhang, C.[Cheng],
Shen, J.[Jun],
Zheng, Z.[Zuduo],
A Dynamic Sensitivity Model for Unidirectional Pedestrian Flow With
Overtaking Behaviour and Its Application on Social Distancing's
Impact During COVID-19,
ITS(23), No. 8, August 2022, pp. 10404-10417.
IEEE DOI
2208
Legged locomotion, Sensitivity, COVID-19, Force, Social factors,
Human factors, Vehicle dynamics, Pedestrian behaviour,
COVID-19
BibRef
Wang, C.[Chao],
Wang, X.[XiaoChen],
Wang, Z.Y.[Zhong-Yuan],
Zhu, W.[WenQian],
Hu, R.M.[Rui-Min],
COVID-19 contact tracking by group activity trajectory recovery over
camera networks,
PR(132), 2022, pp. 108908.
Elsevier DOI
2209
Contact tracking, COVID-19, Group activity, Trajectory recovery
BibRef
Asif, H.[Hafiz],
Papakonstantinou, P.A.[Periklis A.],
Shiau, S.[Stephanie],
Singh, V.[Vivek],
Vaidya, J.[Jaideep],
Intelligent Pandemic Surveillance via Privacy-Preserving Crowdsensing,
IEEE_Int_Sys(37), No. 4, July 2022, pp. 88-96.
IEEE DOI
2209
COVID-19, Privacy, Pandemics, Crowdsensing, Intelligent systems,
Surveillance, Covid-19, pandemic, disease surveillance, crowdsensing,
differential privacy
BibRef
Ghosh, S.[Shreya],
Dhall, A.[Abhinav],
Sebe, N.[Nicu],
Gedeon, T.[Tom],
Automatic Prediction of Group Cohesiveness in Images,
AffCom(13), No. 3, July 2022, pp. 1677-1690.
IEEE DOI
2209
Databases, Feature extraction, Task analysis, Bonding, Faces,
Affective computing, Visualization, Group-level emotion, cohesion estimation
BibRef
Zhang, J.X.[Jia-Xu],
Jia, Y.F.[Yi-Fan],
Xie, W.[Wei],
Tu, Z.G.[Zhi-Gang],
Zoom Transformer for Skeleton-Based Group Activity Recognition,
CirSysVideo(32), No. 12, December 2022, pp. 8646-8659.
IEEE DOI
2212
Transformers, Feature extraction, Activity recognition,
Data mining, Visualization, Task analysis, Activity recognition,
attention mechanism
BibRef
Yan, R.[Rui],
Xie, L.X.[Ling-Xi],
Tang, J.H.[Jin-Hui],
Shu, X.B.[Xiang-Bo],
Tian, Q.[Qi],
HiGCIN: Hierarchical Graph-Based Cross Inference Network for Group
Activity Recognition,
PAMI(45), No. 6, June 2023, pp. 6955-6968.
IEEE DOI
2305
Spatiotemporal phenomena, Activity recognition, Body regions,
Feature extraction, Visualization, Group activity recognition,
video analysis
BibRef
Yan, Y.C.[Yi-Chao],
Qin, J.[Jie],
Ni, B.B.[Bing-Bing],
Chen, J.X.[Jia-Xin],
Liu, L.[Li],
Zhu, F.[Fan],
Zheng, W.S.[Wei-Shi],
Yang, X.K.[Xiao-Kang],
Shao, L.[Ling],
Learning Multi-Attention Context Graph for Group-Based
Re-Identification,
PAMI(45), No. 6, June 2023, pp. 7001-7018.
IEEE DOI
2305
Task analysis, Deep learning, Measurement, Visualization,
Context modeling, Layout, Group re-identification,
graph neural networks
BibRef
Wu, L.F.[Li-Fang],
Lang, X.L.[Xiang-Long],
Xiang, Y.[Ye],
Chen, C.W.[Chang-Wen],
Li, Z.[Zun],
Wang, Z.M.[Zhu-Ming],
Active Spatial Positions Based Hierarchical Relation Inference for
Group Activity Recognition,
CirSysVideo(33), No. 6, June 2023, pp. 2839-2851.
IEEE DOI
2306
Activity recognition, Feature extraction, Visualization, Testing,
Training, Task analysis, Labeling, Group activity recognition,
hierarchical relation inference
BibRef
Zhu, X.L.[Xiao-Lin],
Zhou, Y.[Yan],
Wang, D.[Dongli],
Ouyang, W.L.[Wan-Li],
Su, R.[Rui],
MLST-Former: Multi-Level Spatial-Temporal Transformer for Group
Activity Recognition,
CirSysVideo(33), No. 7, July 2023, pp. 3383-3397.
IEEE DOI
2307
Activity recognition, Transformers, Task analysis, Trajectory,
Feature extraction, Dynamics, Context modeling,
spatial-temporal transformer
BibRef
Spitzley, L.A.[Lee A.],
Wang, X.R.[Xin-Ran],
Chen, X.[Xunyu],
Pentland, S.J.[Steven J.],
Nunamaker, J.F.[Jay F.],
Burgoon, J.K.[Judee K.],
Dunbar, N.E.[Norah E.],
Non-Invasive Measurement of Trust in Group Interactions,
AffCom(14), No. 3, July 2023, pp. 2389-2401.
IEEE DOI
2310
BibRef
Du, Z.X.[Ze-Xing],
Wang, X.[Xue],
Wang, Q.[Qing],
Perceiving local relative motion and global correlations for weakly
supervised group activity recognition,
IVC(137), 2023, pp. 104789.
Elsevier DOI
2309
Group activity recognition, Local relative motion information,
Weakly supervision, Global correlations
BibRef
Du, Z.X.[Ze-Xing],
Wang, X.[Xue],
Wang, Q.[Qing],
Self-Supervised Global Spatio-Temporal Interaction Pre-Training for
Group Activity Recognition,
CirSysVideo(33), No. 9, September 2023, pp. 5076-5088.
IEEE DOI
2310
BibRef
Airale, L.[Louis],
Vaufreydaz, D.[Dominique],
Alameda-Pineda, X.[Xavier],
SocialInteractionGAN: Multi-Person Interaction Sequence Generation,
AffCom(14), No. 3, July 2023, pp. 2182-2192.
IEEE DOI
2310
BibRef
Pei, D.X.[Duo-Xuan],
Huang, D.[Di],
Kong, L.T.[Long-Teng],
Wang, Y.H.[Yun-Hong],
Key Role Guided Transformer for Group Activity Recognition,
CirSysVideo(33), No. 12, December 2023, pp. 7803-7818.
IEEE DOI
2312
BibRef
Kong, L.T.[Long-Teng],
Zhou, W.T.[Wan-Ting],
Pei, D.X.[Duo-Xuan],
He, Z.F.[Zhao-Feng],
Huang, D.[Di],
Group Activity Representation Learning With Long-Short States
Predictive Transformer,
CirSysVideo(33), No. 12, December 2023, pp. 7267-7281.
IEEE DOI
2312
BibRef
Zhou, W.T.[Wan-Ting],
Kong, L.[Longteng],
Han, Y.S.[Yu-Shan],
Qin, J.[Jie],
Sun, Z.A.[Zhen-An],
Contextualized Relation Predictive Model for Self-Supervised Group
Activity Representation Learning,
MultMed(26), 2024, pp. 353-366.
IEEE DOI
2402
Videos, Transformers, Predictive models, Predictive coding,
Context modeling, Task analysis, Feature extraction,
predictive coding
BibRef
Wu, W.H.[Wen-Han],
Yi, W.F.[Wen-Feng],
Li, J.H.[Jing-Hai],
Chen, M.[Maoyin],
Zheng, X.P.[Xiao-Ping],
Automatic Identification of Human Subgroups in Time-Dependent
Pedestrian Flow Networks,
MultMed(26), 2024, pp. 166-177.
IEEE DOI
2401
BibRef
Xie, Z.[Zhao],
Jiao, C.[Chang],
Wu, K.W.[Ke-Wei],
Guo, D.[Dan],
Hong, R.C.[Ri-Chang],
Active Factor Graph Network for Group Activity Recognition,
IP(33), 2024, pp. 1574-1587.
IEEE DOI
2403
Activity recognition, Feature extraction, Adaptation models,
Transformers, Task analysis, Legged locomotion, Visualization,
consistency-aware reasoning
BibRef
Wu, L.F.[Li-Fang],
Tian, M.[Meng],
Xiang, Y.[Ye],
Gu, K.[Ke],
Shi, G.[Ge],
Learning Label Semantics for Weakly Supervised Group Activity
Recognition,
MultMed(26), 2024, pp. 6386-6397.
IEEE DOI
2404
Semantics, Feature extraction, Activity recognition, Annotations,
Encoding, Visualization, Transformers, Multi-Label Classification
BibRef
Jiang, H.[Haoge],
Bhujel, N.[Niraj],
Lin, Z.Y.[Zhuo-Yi],
Wan, K.W.[Kong-Wah],
Li, J.[Jun],
Jayavelu, S.[Senthilnath],
Jiang, X.D.[Xu-Dong],
Learning Relation in Crowd Using Gated Graph Convolutional Networks
for DRL-Based Robot Navigation,
ITS(25), No. 6, June 2024, pp. 5085-5095.
IEEE DOI
2406
Robots, Navigation, Collision avoidance, Pedestrians, Reinforcement learning,
Convolutional neural networks, autonomous unmanned vehicles
BibRef
Du, Z.X.[Ze-Xing],
Wang, Q.[Qing],
Exploring global context and position-aware representation for group
activity recognition,
IVC(149), 2024, pp. 105181.
Elsevier DOI
2408
Group activity recognition, Spatio-temporal representation,
Position-aware representation
BibRef
Maman, L.[Lucien],
Lehmann-Willenbrock, N.[Nale],
Chetouani, M.[Mohamed],
Likforman-Sulem, L.[Laurence],
Varni, G.[Giovanna],
Modeling the Interplay Between Cohesion Dimensions:
A Challenge for Group Affective Emergent States,
AffCom(15), No. 3, July 2024, pp. 1526-1538.
IEEE DOI
2409
Task analysis, Behavioral sciences, Predictive models,
Affective computing, Computational modeling, transfer learning
BibRef
Chang, C.J.[Che-Jui],
Li, D.[Danrui],
Patel, D.[Deep],
Goel, P.[Parth],
Zhou, H.[Honglu],
Moon, S.[Seonghyeon],
Sohn, S.S.[Samuel S.],
Yoon, S.[Sejong],
Pavlovic, V.[Vladimir],
Kapadia, M.[Mubbasir],
Learning from Synthetic Human Group Activities,
CVPR24(21922-21932)
IEEE DOI Code:
WWW Link.
2410
Measurement, Costs, Semantics, Generators,
synthetic data, multi-person tracking,
group activity generation
BibRef
Nakatani, C.[Chihiro],
Kawashima, H.[Hiroaki],
Ukita, N.[Norimichi],
Learning Group Activity Features Through Person Attribute Prediction,
CVPR24(18233-18242)
IEEE DOI Code:
WWW Link.
2410
Visualization, Codes, Annotations, Supervised learning, Manuals,
Feature extraction, group activity recognition,
representation learning
BibRef
Zhang, Y.[Youliang],
Liu, W.X.[Wen-Xuan],
Xu, D.[Danni],
Zhou, Z.[Zhuo],
Wang, Z.[Zheng],
Bi-Causal: Group Activity Recognition via Bidirectional Causality,
CVPR24(1450-1459)
IEEE DOI Code:
WWW Link.
2410
Computational modeling, Cause effect analysis,
Communication channels, Activity recognition,
Human-object relation
BibRef
Bu, Y.F.[Yi-Fan],
Pedestrian flow monitoring system based on Deep learning pipeline,
CVIDL23(395-398)
IEEE DOI
2403
Deep learning, Pedestrians, Target tracking,
Pipelines, Data visualization, Object detection, deep learning,
pedestrian flow monitoring
BibRef
Huang, B.Z.[Bu-Zhen],
Ju, J.Y.[Jing-Yi],
Li, Z.H.[Zhi-Hao],
Wang, Y.G.[Yan-Gang],
Reconstructing Groups of People with Hypergraph Relational Reasoning,
ICCV23(14827-14837)
IEEE DOI Code:
WWW Link.
2401
BibRef
Chappa, N.V.S.R.[Naga V. S. Raviteja],
Nguyen, P.[Pha],
Nelson, A.H.[Alexander H.],
Seo, H.S.[Han-Seok],
Li, X.[Xin],
Dobbs, P.D.[Page Daniel],
Luu, K.[Khoa],
SPARTAN: Self-supervised Spatiotemporal Transformers Approach to
Group Activity Recognition,
CVSports23(5158-5168)
IEEE DOI
2309
BibRef
Xie, Z.[Zhao],
Gao, T.[Tian],
Wu, K.W.[Ke-Wei],
Chang, J.[Jiao],
An Actor-centric Causality Graph for Asynchronous Temporal Inference
in Group Activity,
CVPR23(6652-6661)
IEEE DOI
2309
BibRef
Zhang, S.Y.[Shi-Yi],
Dai, W.X.[Wen-Xun],
Wang, S.[Sujia],
Shen, X.W.[Xiang-Wei],
Lu, J.W.[Ji-Wen],
Zhou, J.[Jie],
Tang, Y.S.[Yan-Song],
LOGO: A Long-Form Video Dataset for Group Action Quality Assessment,
CVPR23(2405-2414)
IEEE DOI
2309
BibRef
Atici, E.[Efehan],
Gökberk, B.[Berk],
Akarun, L.[Lale],
Detection of Free-Standing Conversational Groups with Graph
Convolutional Networks,
ICPR22(1041-1047)
IEEE DOI
2212
Human computer interaction, Social groups, Filtering, Detectors,
Benchmark testing, Behavioral sciences
BibRef
Wang, Y.[Yuan],
Zhang, Q.[Quan],
Lai, J.H.[Jian-Huang],
Xie, X.H.[Xiao-Hua],
Dong, J.H.[Jun-Hao],
Learning Bi-directional Feature Propagation with Latent Layout
Modeling for Group Re-identification,
ICPR22(907-913)
IEEE DOI
2212
Layout, Bidirectional control, Feature extraction, Cameras
BibRef
Zhou, H.[Honglu],
Kadav, A.[Asim],
Shamsian, A.[Aviv],
Geng, S.J.[Shi-Jie],
Lai, F.[Farley],
Zhao, L.[Long],
Liu, T.[Ting],
Kapadia, M.[Mubbasir],
Graf, H.P.[Hans Peter],
COMPOSER: Compositional Reasoning of Group Activity in Videos with
Keypoint-Only Modality,
ECCV22(XXXV:249-266).
Springer DOI
2211
BibRef
Li, J.C.[Jia-Cheng],
Han, R.[Ruize],
Yan, H.M.[Hao-Min],
Qian, Z.K.[Ze-Kun],
Feng, W.[Wei],
Wang, S.[Song],
Self-supervised Social Relation Representation for Human Group
Detection,
ECCV22(XXXV:142-159).
Springer DOI
2211
BibRef
Zhou, Z.K.[Zi-Kang],
Ye, L.[Luyao],
Wang, J.P.[Jian-Ping],
Wu, K.[Kui],
Lu, K.J.[Ke-Jie],
HiVT: Hierarchical Vector Transformer for Multi-Agent Motion
Prediction,
CVPR22(8813-8823)
IEEE DOI
2210
Tracking, Computational modeling,
Predictive models, Benchmark testing, Transformers,
Navigation and autonomous driving
BibRef
Ehsanpour, M.[Mahsa],
Saleh, F.[Fatemeh],
Savarese, S.[Silvio],
Reid, I.D.[Ian D.],
Rezatofighi, H.[Hamid],
JRDB-Act: A Large-scale Dataset for Spatio-temporal Action, Social
Group and Activity Detection,
CVPR22(20951-20960)
IEEE DOI
2210
Visualization, Social groups, Annotations, Pipelines, Social robots,
Robot sensing systems,
Video analysis and understanding
BibRef
Kim, D.[Dongkeun],
Lee, J.[Jinsung],
Cho, M.[Minsu],
Kwak, S.[Suha],
Detector-Free Weakly Supervised Group Activity Recognition,
CVPR22(20051-20061)
IEEE DOI
2210
Image analysis, Computational modeling, Supervised learning,
Detectors, Activity recognition, Benchmark testing,
Video analysis and understanding
BibRef
Zhang, Q.[Quan],
Dang, K.[Kaiheng],
Lai, J.H.[Jian-Huang],
Feng, Z.X.[Zhan-Xiang],
Xie, X.H.[Xiao-Hua],
Modeling 3D Layout For Group Re-Identification,
CVPR22(7502-7510)
IEEE DOI
2210
Solid modeling, Annotations, Layout, Resists, Feature extraction,
Recognition: detection, categorization, retrieval, Representation learning
BibRef
Hao, Y.B.[Yan-Bin],
Zhang, H.[Hao],
Ngo, C.W.[Chong-Wah],
He, X.N.[Xiang-Nan],
Group Contextualization for Video Recognition,
CVPR22(918-928)
IEEE DOI
2210
Solid modeling, Costs, Codes, Computational modeling, Refining,
Recognition: detection, categorization, retrieval,
Efficient learning and inferences
BibRef
Han, M.F.[Ming-Fei],
Zhang, D.J.H.[David Jun-Hao],
Wang, Y.[Yali],
Yan, R.[Rui],
Yao, L.[Lina],
Chang, X.J.[Xiao-Jun],
Qiao, Y.[Yu],
Dual-AI: Dual-path Actor Interaction Learning for Group Activity
Recognition,
CVPR22(2980-2989)
IEEE DOI
2210
Training data, Data visualization, Activity recognition,
Benchmark testing, Transformers,
Action and event recognition
BibRef
Li, S.C.[Shuai-Cheng],
Cao, Q.G.[Qiang-Gang],
Liu, L.B.[Ling-Bo],
Yang, K.L.[Kun-Lin],
Liu, S.[Shinan],
Hou, J.[Jun],
Yi, S.[Shuai],
GroupFormer: Group Activity Recognition with Clustered
Spatial-Temporal Transformer,
ICCV21(13648-13657)
IEEE DOI
2203
Bridges, Codes, Semantics,
Activity recognition, Benchmark testing,
Video analysis and understanding
BibRef
Yuan, H.J.[Hang-Jie],
Ni, D.[Dong],
Wang, M.[Mang],
Spatio-Temporal Dynamic Inference Network for Group Activity
Recognition,
ICCV21(7456-7465)
IEEE DOI
2203
Costing, Computational modeling, Activity recognition,
Spatiotemporal phenomena, Video analysis and understanding,
Scene analysis and understanding
BibRef
Nakatani, C.[Chihiro],
Kawashima, H.[Hiroaki],
Ukita, N.[Norimichi],
Joint Learning with Group Relation and Individual Action,
MVA23(1-6)
DOI Link
2403
Annotations, Machine vision, Supervised learning, Manuals, Feature extraction
BibRef
Nakatani, C.[Chihiro],
Sendo, K.[Kohei],
Ukita, N.[Norimichi],
Group Activity Recognition Using Joint Learning of Individual Action
Recognition and People Grouping,
MVA21(1-5)
DOI Link
2109
Activity recognition, Task analysis
BibRef
Pei, D.X.[Duo-Xuan],
Li, A.[Annan],
Wang, Y.H.[Yun-Hong],
Group Activity Recognition by Exploiting Position Distribution and
Appearance Relation,
MMMod21(I:123-135).
Springer DOI
2106
BibRef
Lu, L.H.[Li-Hua],
Lu, Y.[Yao],
Wang, S.Z.[Shun-Zhou],
Learning Multi-level Interaction Relations and Feature Representations
for Group Activity Recognition,
MMMod21(I:617-628).
Springer DOI
2106
BibRef
Mei, L.[Ling],
Lai, J.H.[Jian-Huang],
Feng, Z.X.[Zhan-Xiang],
Xie, X.H.[Xiao-Hua],
Open-World Group Retrieval with Ambiguity Removal: A Benchmark,
ICPR21(584-591)
IEEE DOI
2105
Visualization, Benchmark testing, Cameras, Feature extraction,
Robustness, Probes
BibRef
Dasgupta, A.[Avijit],
Jawahar, C.V.,
Alahari, K.[Karteek],
Context Aware Group Activity Recognition,
ICPR21(10098-10105)
IEEE DOI
2105
Context-aware services, Activity recognition, Benchmark testing,
Task analysis, Videos, Sports, Context modeling
BibRef
Zappardino, F.[Fabio],
Uricchio, T.[Tiberio],
Seidenari, L.[Lorenzo],
del Bimbo, A.[Alberto],
Learning Group Activities from Skeletons without Individual Action
Labels,
ICPR21(10412-10417)
IEEE DOI
2105
Data privacy, Art, Annotations, Computational modeling,
Activity recognition, Feature extraction
BibRef
Jia, B.X.[Bao-Xiong],
Chen, Y.X.[Yi-Xin],
Huang, S.Y.[Si-Yuan],
Zhu, Y.X.[Yi-Xin],
Zhu, S.C.[Song-Chun],
Lemma: A Multi-view Dataset for Learning Multi-agent Multi-task
Activities,
ECCV20(XXVI:767-786).
Springer DOI
2011
BibRef
Chen, J.W.[Jun-Wen],
Bao, W.T.[Wen-Tao],
Kong, Y.[Yu],
Group Activity Prediction with Sequential Relational Anticipation Model,
ECCV20(XXI:581-597).
Springer DOI
2011
BibRef
Yan, R.[Rui],
Xie, L.X.[Ling-Xi],
Tang, J.H.[Jin-Hui],
Shu, X.B.[Xiang-Bo],
Tian, Q.[Qi],
Social Adaptive Module for Weakly-supervised Group Activity Recognition,
ECCV20(VIII:208-224).
Springer DOI
2011
BibRef
Shi, Z.S.[Zhen-Sheng],
Guan, C.[Cheng],
Cao, L.J.[Liang-Jie],
Li, Q.Q.[Qian-Qian],
Liang, J.[Ju],
Gu, Z.R.[Zhao-Rui],
Zheng, H.Y.[Hai-Yong],
Zheng, B.[Bing],
CoTeRe-net: Discovering Collaborative Ternary Relations in Videos,
ECCV20(VI:379-396).
Springer DOI
2011
Code, Action Recognition.
WWW Link. Relations for action and behavior recognition.
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Guo, X.,
Polanía, L.F.,
Zhu, B.,
Boncelet, C.,
Barner, K.E.,
Graph Neural Networks for Image Understanding Based on Multiple Cues:
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WACV20(2910-2919)
IEEE DOI
2006
Feature extraction, Task analysis, Emotion recognition,
Image recognition, Neural networks, Streaming media, Data mining
BibRef
Graber, C.,
Schwing, A.G.,
Dynamic Neural Relational Inference,
CVPR20(8510-8519)
IEEE DOI
2008
Decoding, Trajectory, Predictive models, Forecasting, History, Task analysis
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Gavrilyuk, K.,
Sanford, R.,
Javan, M.,
Snoek, C.G.M.,
Actor-Transformers for Group Activity Recognition,
CVPR20(836-845)
IEEE DOI
2008
Videos, Activity recognition,
Feature extraction, Task analysis, Data mining
BibRef
Hu, G.,
Cui, B.,
He, Y.,
Yu, S.,
Progressive Relation Learning for Group Activity Recognition,
CVPR20(977-986)
IEEE DOI
2008
Semantics, Spatiotemporal phenomena, Artificial neural networks,
Feature extraction, Logic gates, Visualization
BibRef
Chen, J.,
Hao, H.,
Hong, H.,
Kong, Y.,
RIT-18: A Novel Dataset for Compositional Group Activity
Understanding,
WiCV20(1488-1494)
IEEE DOI
2008
Activity recognition, Games, Videos, Task analysis, Surveillance, YouTube
BibRef
Li, J.N.[Jun-Nan],
Liu, J.Q.[Jian-Quan],
Wang, Y.K.[Yong-Kang],
Nishimura, S.[Shoji],
Kankanhalli, M.S.[Mohan S.],
Weakly-Supervised Multi-Person Action Recognition in 360° Videos,
WACV20(497-505)
IEEE DOI
2006
Videos, Cameras, Feature extraction,
Radio frequency, Transforms, Training
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Stephen, K.[Karen],
Liu, J.Q.[Jian-Quan],
Barsopia, V.[Vivek],
A Hybrid two-stream approach for Multi-Person Action Recognition in
TOP-VIEW 360° Videos,
ICIP21(3418-3422)
IEEE DOI
2201
Image recognition, Art, Transforms,
Streaming media, 360° video analysis, action recognition
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Rhodin, H.[Helge],
Constantin, V.[Victor],
Katircioglu, I.[Isinsu],
Salzmann, M.[Mathieu],
Fua, P.[Pascal],
Neural Scene Decomposition for Multi-Person Motion Capture,
CVPR19(7695-7705).
IEEE DOI
2002
BibRef
Azar, S.M.[Sina Mokhtarzadeh],
Atigh, M.G.[Mina Ghadimi],
Nickabadi, A.[Ahmad],
Alahi, A.[Alexandre],
Convolutional Relational Machine for Group Activity Recognition,
CVPR19(7884-7893).
IEEE DOI
2002
BibRef
Wu, J.C.[Jian-Chao],
Wang, L.M.[Li-Min],
Wang, L.[Li],
Guo, J.[Jie],
Wu, G.S.[Gang-Shan],
Learning Actor Relation Graphs for Group Activity Recognition,
CVPR19(9956-9966).
IEEE DOI
2002
BibRef
Sendo, K.,
Ukita, N.,
Heatmapping of People Involved in Group Activities,
MVA19(1-6)
DOI Link
1911
image colour analysis, image segmentation, people grouping,
group activity, heatmapping people, deep network,
Approximation algorithms
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Akar, A.[Arif],
Ikizler-Cinbis, N.[Nazli],
Mask Guided Fusion for Group Activity Recognition in Images,
CIAP19(II:282-291).
Springer DOI
1909
BibRef
Krishna, R.[Ranjay],
Chami, I.[Ines],
Bernstein, M.[Michael],
Fei-Fei, L.[Li],
Referring Relationships,
CVPR18(6867-6876)
IEEE DOI
1812
Visualization, Task analysis, Semantics, Marine vehicles,
Feature extraction, Genomics
BibRef
Fan, L.F.[Li-Feng],
Chen, Y.X.[Yi-Xin],
Wei, P.[Ping],
Wang, W.G.[Wen-Guan],
Zhu, S.C.[Song-Chun],
Inferring Shared Attention in Social Scene Videos,
CVPR18(6460-6468)
IEEE DOI
1812
Videos, TV, Head, Task analysis, Motion pictures
BibRef
Ibrahim, M.S.[Mostafa S.],
Mori, G.[Greg],
Hierarchical Relational Networks for Group Activity Recognition and
Retrieval,
ECCV18(III: 742-758).
Springer DOI
1810
BibRef
Tang, Y.,
Zhang, P.,
Hu, J.F.,
Zheng, W.S.,
Latent embeddings for collective activity recognition,
AVSS17(1-6)
IEEE DOI
1806
feature extraction, image recognition,
learning (artificial intelligence), video signal processing,
Visualization
BibRef
Biswas, S.[Sovan],
Gall, J.[Juergen],
Discovering Multi-label Actor-Action Association in a Weakly Supervised
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ACCV20(V:547-561).
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2103
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Biswas, S.[Sovan],
Gall, J.[Juergen],
Structural Recurrent Neural Network (SRNN) for Group Activity
Analysis,
WACV18(1625-1632)
IEEE DOI
1806
image motion analysis, recurrent neural nets,
SRNN, group activity analysis, interconnected RNN,
Videos
BibRef
Li, X.,
Chuah, M.C.[Mooi Choo],
SBGAR: Semantics Based Group Activity Recognition,
ICCV17(2895-2904)
IEEE DOI
1802
feature extraction, image recognition,
object recognition, video signal processing,
Predictive models
BibRef
Wang, M.,
Ni, B.,
Yang, X.,
Recurrent Modeling of Interaction Context for Collective Activity
Recognition,
CVPR17(7408-7416)
IEEE DOI
1711
Activity recognition, Computational modeling, Context modeling,
Encoding, Feature extraction, Logic gates, Tracking
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Shu, T.,
Todorovic, S.,
Zhu, S.C.,
CERN: Confidence-Energy Recurrent Network for Group Activity
Recognition,
CVPR17(4255-4263)
IEEE DOI
1711
Activity recognition, Reliability, Training,
Training data, Trajectory, Videos
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Ienaga, N.,
Ozasa, Y.,
Saito, H.,
Speaker Identification Based on Integrated Face Direction in a Group
Conversation,
HAAHDC17(53-57)
IEEE DOI
1609
face recognition, speaker recognition, group conversation,
group members, integrated face direction,
vision-based speaker identification, Context, Context modeling,
Face, Kernel, Robots, Support vector machines, Training, data
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Denzler, J.[Joachim],
Unsupervised Group Activity Detection by Hierarchical Dirichlet
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ICIAR17(399-407).
Springer DOI
1706
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Zhang, L.,
Hung, H.,
Beyond F-Formations: Determining Social Involvement in Free Standing
Conversing Groups from Static Images,
CVPR16(1086-1095)
IEEE DOI
1612
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Dihl, L.,
Barreto, R.,
Musse, S.R.,
Using group behaviors to detect Hofstede cultural dimensions,
ICIP16(2936-2940)
IEEE DOI
1610
Computer vision
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Liu, Q.,
da Campos, T.,
Wang, W.,
Jackson, P.J.B.[Philip J. B.],
Hilton, A.[Adrian],
Person Tracking Using Audio and Depth Cues,
3DVS15(709-717)
IEEE DOI
1602
Atmospheric measurements
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Vahdat, A.,
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Mori, G.[Greg],
Structure Inference Machines: Recurrent Neural Networks for Analyzing
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CVPR16(4772-4781)
IEEE DOI
1612
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Deng, Z.,
Ibrahim, M.S.,
Mori, G.,
Generic Tubelet Proposals for Action Localization,
WACV18(343-351)
IEEE DOI
1806
image classification, image motion analysis, object detection,
video signal processing, J-HMDB21 dataset, L1 loss function, TPN,
Videos
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Muralidharan, S.[Srikanth],
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CVPR16(1971-1980)
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1612
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Truong, K.P.[Khiet P.],
Charisi, V.[Vicky],
Zaga, C.[Cristina],
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Multimodal Detection of Engagement in Groups of Children Using Rank
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HBU16(35-48).
Springer DOI
1611
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Zhai, M.Y.[Meng-Yao],
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Mori, G.[Greg],
Deep Structured Models For Group Activity Recognition,
BMVC15(xx-yy).
DOI Link
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IbPRIA15(13-22).
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1506
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ACCV14(V: 508-521).
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1504
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Activity Group Localization by Modeling the Relations among
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ECCV14(I: 741-755).
Springer DOI
1408
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1408
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CVPR12(2208-2215).
IEEE DOI
1208
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IEEE DOI
0906
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Multi-scale f-formation discovery for group detection,
ICIP13(3547-3551)
IEEE DOI
1402
F-formation; group detection; group detection metrics
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Burkert, F.,
Fraundorfer, F.,
UAV-Based Monitoring of Pedestrian Groups,
UAV-g13(67-72).
DOI Link
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ICIP12(2709-2712).
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1302
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Group Dynamics and Multimodal Interaction Modeling Using a Smart
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VECTaR12(I: 362-371).
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1210
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Group Tracking: Exploring Mutual Relations for Multiple Object Tracking,
ECCV12(III: 129-143).
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1210
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Group context learning for event recognition,
WACV12(249-255).
IEEE DOI
1203
Award, WACV, Student. motion and interaction of members in a group
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1201
Who is the leader?
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1108
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ICPR10(3228-3231).
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1008
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Group Action Recognition Using Space-Time Interest Points,
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0906
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0801
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IEEE DOI
0602
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0303
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Classifying and Detecting Group Behaviour from
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IEEE DOI
9808
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Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Social Interactions, Human Activities, Social Grouping .