17.1.3.7 Human Activity Recognition, Human Behaviors

Chapter Contents (Back)
Activity Recognition. Event Recognition. Generally more an extended activity rather than a basic action.
See also Complex Human Activity Recognition.
See also Human Action Detection, Human Action Recognition.
See also Depth Based, Human Activity Recognition.
See also Models, Inference, Learning Human Activities, Human Behavior.
See also Pedestrian Safety Issues, Pedestrian Behavior.

FCVID: Fudan-Columbia Video Dataset,

WWW Link. Dataset, Activity Recognition. 90,000+ videos, manually annotated for 239 categories. Human activities.

Stauffer, C.[Chris], Grimson, W.E.L.[W. Eric L.],
Learning Patterns of Activity Using Real-Time Tracking,
PAMI(22), No. 8, August 2000, pp. 747-757.
IEEE DOI 0010
Using the 24 hour data from tracking motion, learn the different patterns, especially to see things that don't fit. Motion segmentation uses adaptive background subtraction with an updated model. Objects are not recognized, but identity is maintained throught the track. BibRef

Stauffer, C.[Chris],
Automated Audio-visual Activity Analysis,
CSAIL-2005-057, September 2005.
WWW Link. BibRef 0509

Gong, S.G.[Shao-Gang], Ng, J.[Jeffrey], Sherrah, J.[Jamie],
On the semantics of visual behaviour, structured events and trajectories of human action,
IVC(20), No. 12, October 2002, pp. 873-888.
Elsevier DOI 0210
BibRef

Ng, J., Gong, S.G.[Shao-Gang],
On the binding mechanism of synchronised visual events,
Motion02(112-117).
IEEE DOI 0303
BibRef

Kawanaka, D.[Daiki], Okatani, T.[Takayuki], Deguchi, K.[Koichiro],
HHMM Based Recognition of Human Activity,
IEICE(E89-D), No. 7, July 2006, pp. 2180-2185.
DOI Link 0607
BibRef

Robertson, N.M.[Neil M.], Reid, I.D.[Ian D.],
A general method for human activity recognition in video,
CVIU(103), No. 2-3, November-December 2006, pp. 232-248.
Elsevier DOI 0611
BibRef
Earlier:
Behaviour Understanding in Video: A Combined Method,
ICCV05(I: 808-815).
IEEE DOI 0510
Visual surveillance; Human activity recognition; Video annotation BibRef

Robertson, N.M.[Neil M.], Reid, I.D.[Ian D.],
Automatic Reasoning about Causal Events in Surveillance Video,
JIVP(2011), No. 2011, pp. xx-yy.
DOI Link 1103
BibRef

Hsieh, J.W.[Jun-Wei], Hsu, Y.T.[Yung-Tai],
Boosted string representation and its application to video surveillance,
PR(41), No. 10, October 2008, pp. 3078-3091.
Elsevier DOI 0808
Behavior analysis; Centroid contexts; String matching; Boosting algorithm BibRef

Lin, W., Sun, M.T., Poovendran, R., Zhang, Z.,
Activity Recognition Using a Combination of Category Components and Local Models for Video Surveillance,
CirSysVideo(18), No. 8, August 2008, pp. 1128-1139.
IEEE DOI 0809

See also Group Event Detection With a Varying Number of Group Members for Video Surveillance. BibRef

Shen, J., Tao, D., Li, X.,
Modality Mixture Projections for Semantic Video Event Detection,
CirSysVideo(18), No. 11, November 2008, pp. 1587-1596.
IEEE DOI 0811
BibRef

Duong, T.V.[Thi V.], Phung, D.Q.[Dinh Q.], Bui, H.H.[Hung H.], Venkatesh, S.[Svetha],
Efficient duration and hierarchical modeling for human activity recognition,
AI(173), No. 7-8, May 2009, pp. 830-856.
Elsevier DOI 0904
Duration modeling; Coxian; Hidden semi-Markov model; Human activity recognition; Smart surveillance BibRef

Kim, Y., Ling, H.,
Human Activity Classification Based on Micro-Doppler Signatures Using a Support Vector Machine,
GeoRS(47), No. 5, May 2009, pp. 1328-1337.
IEEE DOI 0904
BibRef

Qian, H.M.[Hui-Min], Mao, Y.B.[Yao-Bin], Xiang, W.B.[Wen-Bo], Wang, Z.Q.[Zhi-Quan],
Recognition of human activities using SVM multi-class classifier,
PRL(31), No. 2, 15 January 2010, pp. 100-111.
Elsevier DOI 1001
Human activity recognition; Background subtraction; CCMEI; Support vector machine; Decision tree classifier BibRef

Benabbas, Y.[Yassine], Ihaddadene, N.[Nacim], Djeraba, C.[Chaabane],
Motion Pattern Extraction and Event Detection for Automatic Visual Surveillance,
JIVP(2011), No. 2011, pp. xx-yy.
DOI Link 1103
BibRef

Benabbas, Y.[Yassine], Lablack, A.[Adel], Ihaddadene, N.[Nacim], Djeraba, C.[Chabane],
Action Recognition Using Direction Models of Motion,
ICPR10(4295-4298).
IEEE DOI 1008
BibRef

Siirtola, P.[Pekka], Koskimäki, H.[Heli], Huikari, V.[Ville], Laurinen, P.[Perttu], Röning, J.[Juha],
Improving the classification accuracy of streaming data using SAX similarity features,
PRL(32), No. 13, 1 October 2011, pp. 1659-1668.
Elsevier DOI 1109
Activity recognition; Classification; Symbolic dynamics; SAX BibRef

Mandal, B.[Bappaditya], Eng, H.L.[How-Lung],
Regularized Discriminant Analysis for Holistic Human Activity Recognition,
IEEE_Int_Sys(27), No. 1, January-February 2012, pp. 21-31.
IEEE DOI 1203
BibRef

Iosifidis, A.[Alexandros], Tefas, A.[Anastasios], Nikolaidis, N.[Nikolaos], Pitas, I.[Ioannis],
Multi-View Human Movement Recognition Based on Fuzzy Distances and Linear Discriminant Analysis,
CVIU(116), No. 3, March 2012, pp. 347-360.
Elsevier DOI 1201
Activity recognition; Multi-view dynemes; Fuzzy vector quantization; Linear discriminant analysis
See also Combining Fuzzy Vector Quantization With Linear Discriminant Analysis for Continuous Human Movement Recognition. BibRef

Kulkarni, K.[Kuldeep], Turaga, P.K.[Pavan K.],
Reconstruction-Free Action Inference from Compressive Imagers,
PAMI(38), No. 4, April 2016, pp. 772-784.
IEEE DOI 1603
BibRef
Earlier:
Recurrence textures for human activity recognition from compressive cameras,
ICIP12(1417-1420).
IEEE DOI 1302
BibRef

Beaudry, C.[Cyrille], Péteri, R.[Renaud], Mascarilla, L.[Laurent],
An efficient and sparse approach for large scale human action recognition in videos,
MVA(27), No. 4, May 2016, pp. 529-543.
WWW Link. 1605
BibRef
Earlier:
Human activity recognition in the semantic simplex of elementary actions,
BMVC15(xx-yy).
DOI Link 1601
BibRef
Earlier:
Action recognition in videos using frequency analysis of critical point trajectories,
ICIP14(1445-1449)
IEEE DOI 1502
Estimation BibRef

Iosifidis, A.[Alexandros], Tefas, A.[Anastasios], Pitas, I.[Ioannis], Gabbouj, M.[Moncef],
Big Media Data Analysis,
SP:IC(59), No. 1, 2017, pp. 105-108.
Elsevier DOI 1711
Big Media Data. BibRef

Mademlis, I., Tefas, A., Pitas, I.,
Summarization of human activity videos using a salient dictionary,
ICIP17(625-629)
IEEE DOI 1803
Clustering algorithms, Dictionaries, Feature extraction, Optimization, Semantics, Videos, Visualization, Video Summarization BibRef

Cao, G.Q.[Guan-Qun], Iosifidis, A.[Alexandros], Gabbouj, M.[Moncef],
Multi-View Nonparametric Discriminant Analysis for Image Retrieval and Recognition,
SPLetters(24), No. 10, October 2017, pp. 1537-1541.
IEEE DOI 1710
Gaussian distribution, image retrieval, nonparametric statistics, optimisation, Gaussian distribution assumption, multiview class structures, optimization criterion, zero-shot recognition, Gaussian distribution, Laplace equations, BibRef

Cao, G.Q.[Guan-Qun], Iosifidis, A.[Alexandros], Chen, K., Gabbouj, M.[Moncef],
Generalized Multi-View Embedding for Visual Recognition and Cross-Modal Retrieval,
Cyber(48), No. 9, September 2018, pp. 2542-2555.
IEEE DOI 1809
feature extraction, graph theory, image recognition, image retrieval, learning (artificial intelligence), visual recognition BibRef

Iosifidis, A.[Alexandros], Tefas, A.[Anastasios], Pitas, I.[Ioannis],
Class-Specific Reference Discriminant Analysis With Application in Human Behavior Analysis,
HMS(45), No. 3, June 2015, pp. 315-326.
IEEE DOI 1506
BibRef
Earlier:
Semi-supervised Classification of Human Actions Based on Neural Networks,
ICPR14(1336-1341)
IEEE DOI 1412
Accuracy; Databases; Neurons; Optimization; Training; Training data; Vectors. Face recognition
See also Multi-View Human Movement Recognition Based on Fuzzy Distances and Linear Discriminant Analysis. BibRef

Iosifidis, A.[Alexandros], Tefas, A.[Anastastios], Pitas, I.[Ioannis],
Kernel Reference Discriminant Analysis,
PRL(49), No. 1, 2014, pp. 85-91.
Elsevier DOI 1410
Kernel Discriminant Analysis BibRef

Holte, M.B., Moeslund, T.B., Nikolaidis, N., Pitas, I.,
3D Human Action Recognition for Multi-view Camera Systems,
3DIMPVT11(342-349).
IEEE DOI 1109
BibRef

Lu, S.Y.[Shi-Yang], Zhang, J.[Jian], Wang, Z.Y.[Zhi-Yong], Feng, D.D.[David Dagan],
Fast human action classification and VOI localization with enhanced sparse coding,
JVCIR(24), No. 2, February 2013, pp. 127-136.
Elsevier DOI 1302
Human action classification; Localization; Sparse coding; Volume of Interest (VOI) BibRef

Yao, T.T.[Ting-Ting], Wang, Z.Y.[Zhi-Yong], Xie, Z.[Zhao], Gao, J.[Jun], Feng, D.D.[David Dagan],
Learning universal multiview dictionary for human action recognition,
PR(64), No. 1, 2017, pp. 236-244.
Elsevier DOI 1701
Dictionary learning BibRef

Chakraborty, B.[Bhaskar], Gonzàlez, J.[Jordi], Roca, F.X.[F. Xavier],
Large scale continuous visual event recognition using max-margin Hough transformation framework,
CVIU(117), No. 10, 2013, pp. 1356-1368.
Elsevier DOI 1309
Continuous visual event BibRef

Melfi, R.[Roberto], Kondra, S.[Shripad], Petrosino, A.[Alfredo],
Human activity modeling by spatio temporal textural appearance,
PRL(34), No. 15, 2013, pp. 1990-1994.
Elsevier DOI 1309
Human action modeling BibRef

Wang, H.R.[Hao-Ran], Yuan, C.F.[Chun-Feng], Hu, W.M.[Wei-Ming], Ling, H.B.[Hai-Bin], Yang, W.K.[Wan-Kou], Sun, C.Y.[Chang-Yin],
Action Recognition Using Nonnegative Action Component Representation and Sparse Basis Selection,
IP(23), No. 2, February 2014, pp. 570-581.
IEEE DOI 1402
graph theory BibRef

Chen, H.S.[Hsuan-Sheng], Tsai, W.J.[Wen-Jiin],
A framework for video event classification by modeling temporal context of multimodal features using HMM,
JVCIR(25), No. 2, 2014, pp. 285-295.
Elsevier DOI 1402
Multimedia system BibRef

Myers, G.K.[Gregory K.], Nallapati, R.[Ramesh], van Hout, J.[Julien], Pancoast, S.[Stephanie], Nevatia, R.[Ramakant], Sun, C.[Chen], Habibian, A.[Amirhossein], Koelma, D.C.[Dennis C.], van de Sande, K.E.A.[Koen E. A.], Smeulders, A.W.M.[Arnold W. M.], Snoek, C.G.M.[Cees G. M.],
Evaluating multimedia features and fusion for example-based event detection,
MVA(25), No. 1, January 2014, pp. 17-32.
Springer DOI 1402
Overview of large project. BibRef

Kovvuri, R.[Rama], Nevatia, R.[Ram], Snoek, C.G.M.[Cees G. M.],
Segment-based models for event detection and recounting,
ICPR16(3868-3873)
IEEE DOI 1705
Computational modeling, Detectors, Dictionaries, Hidden Markov models, Semantics, Testing, Training BibRef

Chen, K.[Kan], Kovvuri, R.[Rama], Gao, J.Y.[Ji-Yang], Nevatia, R.[Ram],
MSRC: multimodal spatial regression with semantic context for phrase grounding,
MultInfoRetr(8), No. 1, March 2018, pp. 17-28.
Springer DOI 1802
BibRef
Earlier: A1, A2, A4, Only:
Query-Guided Regression Network with Context Policy for Phrase Grounding,
ICCV17(824-832)
IEEE DOI 1802
document image processing, learning (artificial intelligence), query processing, regression analysis, Context Policy Network, Localize the object based on query phrases. BibRef

Kovvuri, R.[Rama], Nevatia, R.[Ram],
PIRC Net: Using Proposal Indexing, Relationships and Context for Phrase Grounding,
ACCV18(IV:451-467).
Springer DOI 1906
BibRef

Agharwal, A.[Arnav], Kovvuri, R.[Rama], Nevatia, R.[Ram], Snoek, C.G.M.[Cees G. M.],
Tag-based video retrieval by embedding semantic content in a continuous word space,
WACV16(1-8)
IEEE DOI 1511
event retrieval in unconstrained web videos. Detectors BibRef

Habibian, A.[Amirhossein], Snoek, C.G.M.[Cees G.M.],
Recommendations for recognizing video events by concept vocabularies,
CVIU(124), No. 1, 2014, pp. 110-122.
Elsevier DOI 1406
Event recognition BibRef

Habibian, A.[Amirhossein], Mensink, T., Snoek, C.G.M.[Cees G.M.],
Video2vec Embeddings Recognize Events When Examples Are Scarce,
PAMI(39), No. 10, October 2017, pp. 2089-2103.
IEEE DOI 1709
Correlation, Feature extraction, NIST, Semantics, Training, Vehicles, Visualization, Event recognition, representation learning, semantic, video, representation BibRef

Oh, S.M.[Sang-Min], McCloskey, S.[Scott], Kim, I.[Ilseo], Vahdat, A.[Arash], Cannons, K.J.[Kevin J.], Hajimirsadeghi, H.[Hossein], Mori, G.[Greg], Perera, A.G.A.[A. G. Amitha], Pandey, M.[Megha], Corso, J.J.[Jason J.],
Multimedia event detection with multimodal feature fusion and temporal concept localization,
MVA(25), No. 1, January 2014, pp. 49-69.
Springer DOI 1402
BibRef

Streib, K.[Kevin], Davis, J.W.[James W.],
Summarizing high-level scene behavior,
MVA(25), No. 1, January 2014, pp. 229-244.
Springer DOI 1402
Both optical flow and trajectories to summarize.
See also Exploiting Multiple Cameras for Environmental Pathlets. BibRef

O'Malley, M.K., Purkayastha, S.N., Howie, N., Byrne, M.D.,
Identifying Successful Motor Task Completion via Motion-Based Performance Metrics,
HMS(44), No. 1, February 2014, pp. 139-145.
IEEE DOI 1403
control engineering computing BibRef

Lin, W.Y., Chen, Y.Z., Wu, J., Wang, H., Sheng, B., Li, H.X.,
A New Network-Based Algorithm for Human Activity Recognition in Videos,
CirSysVideo(24), No. 5, May 2014, pp. 826-841.
IEEE DOI 1405
Correlation BibRef

Chen, Y.Z.[Yuan-Zhe], Lin, W.Y.[Wei-Yao], Li, H.X.[Hong-Xiang], Luo, H.Z.[Hang-Zai], Tao, Y.[Yisi], Liu, D.H.[Dong-Hua],
A new package-group-transmission-based algorithm for human activity recognition in videos,
VCIP11(1-4).
IEEE DOI 1201
BibRef

Kwak, S.[Suha], Han, B.H.[Bo-Hyung], Han, J.H.[Joon Hee],
On-Line Video Event Detection by Constraint Flow,
PAMI(36), No. 6, June 2014, pp. 1174-1186.
IEEE DOI 1406
BibRef
Earlier:
Multi-agent Event Detection: Localization and Role Assignment,
CVPR13(2682-2689)
IEEE DOI 1309
Event detection. activity detection; video event detection BibRef

Ferrer, G.[Gonzalo], Sanfeliu, A.[Alberto],
Bayesian Human Motion Intentionality Prediction in urban environments,
PRL(44), No. 1, 2014, pp. 134-140.
Elsevier DOI 1407
Human motion prediction BibRef

Fouhey, D.F.[David F.], Delaitre, V.[Vincent], Gupta, A.[Abhinav], Efros, A.A.[Alexei A.], Laptev, I.[Ivan], Sivic, J.[Josef],
People Watching: Human Actions as a Cue for Single View Geometry,
IJCV(110), No. 1, December 2014, pp. 259-274.
Springer DOI 1411
BibRef
Earlier: ECCV12(V: 732-745).
Springer DOI 1210
BibRef

Delaitre, V.[Vincent], Fouhey, D.F.[David F.], Laptev, I.[Ivan], Sivic, J.[Josef], Gupta, A.[Abhinav], Efros, A.A.[Alexei A.],
Scene Semantics from Long-Term Observation of People,
ECCV12(VI: 284-298).
Springer DOI 1210
BibRef

Yu, G.[Gang], Yuan, J.S.[Jun-Song], Liu, Z.C.[Zi-Cheng],
Propagative Hough Voting for Human Activity Detection and Recognition,
CirSysVideo(25), No. 1, January 2015, pp. 87-98.
IEEE DOI 1502
BibRef
Earlier:
Propagative Hough Voting for Human Activity Recognition,
ECCV12(III: 693-706).
Springer DOI 1210
feature extraction BibRef

Yang, D.Q.[Ding-Qi], Zhang, D.Q.[Da-Qing], Zheng, V.W., Yu, Z.Y.[Zhi-Yong],
Modeling User Activity Preference by Leveraging User Spatial Temporal Characteristics in LBSNs,
SMCS(45), No. 1, January 2015, pp. 129-142.
IEEE DOI 1502
mobile computing. Tracking info not image based. BibRef

Baxter, R.H.[Rolf H.], Robertson, N.M.[Neil M.], Lane, D.M.[David M.],
Human behaviour recognition in data-scarce domains,
PR(48), No. 8, 2015, pp. 2377-2393.
Elsevier DOI 1505
Behavior recognition BibRef

Chuang, C.H.[Chi-Hung], Hsieh, J.W.[Jun-Wei], Chiang, H.F.[Hui-Fen], Chiou, Y.D.[Yi-Da],
Human movement analysis around a view circle using time-order similarity distributions,
JVCIR(30), No. 1, 2015, pp. 22-34.
Elsevier DOI 1507
Video surveillance BibRef

Jiang, Y.G., Dai, Q., Mei, T., Rui, Y., Chang, S.F.,
Super Fast Event Recognition in Internet Videos,
MultMed(17), No. 8, August 2015, pp. 1174-1186.
IEEE DOI 1506
Feature extraction BibRef

Lee, K.[Kyuhwa], Ognibene, D., Chang, H.J.[Hyung Jin], Kim, T.K.[Tae-Kyun], Demiris, Y.,
STARE: Spatio-Temporal Attention Relocation for Multiple Structured Activities Detection,
IP(24), No. 12, December 2015, pp. 5916-5927.
IEEE DOI 1512
computer vision BibRef

Anirudh, R.[Rushil], Turaga, P.K.[Pavan K.],
Geometry-Based Symbolic Approximation for Fast Sequence Matching on Manifolds,
IJCV(116), No. 2, January 2016, pp. 161-173.
Springer DOI 1602
BibRef

Arai, A.[Ayumi], Fan, Z.[Zipei], Matekenya, D.[Dunstan], Shibasaki, R.[Ryosuke],
Comparative Perspective of Human Behavior Patterns to Uncover Ownership Bias among Mobile Phone Users,
IJGI(5), No. 6, 2016, pp. 85.
DOI Link 1608
BibRef

Barrett, D.P.[Daniel Paul], Barbu, A.[Andrei], Siddharth, N., Siskind, J.M.[Jeffrey Mark],
Saying What You're Looking For: Linguistics Meets Video Search,
PAMI(38), No. 10, October 2016, pp. 2069-2081.
IEEE DOI 1609
BibRef
Earlier: A3, A2, A4, Only:
Seeing What You're Told: Sentence-Guided Activity Recognition in Video,
CVPR14(732-739)
IEEE DOI 1409
Detectors. Text (language) guided analysis. BibRef

Barrett, D.P.[Daniel Paul], Siskind, J.M.[Jeffrey Mark],
Action Recognition by Time Series of Retinotopic Appearance and Motion Features,
CirSysVideo(26), No. 12, December 2016, pp. 2250-2263.
IEEE DOI 1612
Computational modeling BibRef

Guo, Y.[Yanan], Tao, D.P.[Da-Peng], Cheng, J.[Jun], Dougherty, A.[Alan], Li, Y.T.[Yao-Tang], Yue, K.[Kun], Zhang, B.[Bob],
Tensor Manifold Discriminant Projections for Acceleration-Based Human Activity Recognition,
MultMed(18), No. 10, October 2016, pp. 1977-1987.
IEEE DOI 1610
feature extraction BibRef

de Souza, F.D.M.[Fillipe D. M.], Sarkar, S.[Sudeep], Srivastava, A.[Anuj], Su, J.Y.[Jing-Yong],
Spatially Coherent Interpretations of Videos Using Pattern Theory,
IJCV(121), No. 1, January 2017, pp. 5-25.
Springer DOI 1702
BibRef
Earlier:
Temporally coherent interpretations for long videos using pattern theory,
CVPR15(1229-1237)
IEEE DOI 1510
BibRef
Earlier:
Pattern Theory-Based Interpretation of Activities,
ICPR14(106-111)
IEEE DOI 1412
BibRef

Aakur, S.N.[Sathyanarayanan N.], Sarkar, S.[Sudeep],
A Perceptual Prediction Framework for Self Supervised Event Segmentation,
CVPR19(1197-1206).
IEEE DOI 2002
BibRef

Aakur, S.N.[Sathyanarayanan N.], de Souza, F.D.M.[Fillipe D. M.], Sarkar, S.[Sudeep],
Going Deeper With Semantics: Video Activity Interpretation Using Semantic Contextualization,
WACV19(190-199)
IEEE DOI 1904
BibRef
Earlier:
Towards a Knowledge-Based Approach for Generating Video Descriptions,
CRV17(24-31)
IEEE DOI 1804
common-sense reasoning, knowledge based systems, semantic networks, video signal processing, Knowledge based systems. hidden Markov models, learning (artificial intelligence), Semantic coherence BibRef

Azhar, F., Li, C.T.,
Hierarchical Relaxed Partitioning System for Activity Recognition,
Cyber(47), No. 3, March 2017, pp. 784-795.
IEEE DOI 1702
Computational modeling BibRef

Wang, L., Zhao, X., Si, Y., Cao, L., Liu, Y.,
Context-Associative Hierarchical Memory Model for Human Activity Recognition and Prediction,
MultMed(19), No. 3, March 2017, pp. 646-659.
IEEE DOI 1702
Computational modeling BibRef

Wang, B.Y.[Bo-Yue], Hu, Y.L.[Yong-Li], Gao, J.B.[Jun-Bin], Sun, Y.F.[Yan-Feng], Yin, B.C.[Bao-Cai],
Laplacian LRR on Product Grassmann Manifolds for Human Activity Clustering in Multicamera Video Surveillance,
CirSysVideo(27), No. 3, March 2017, pp. 554-566.
IEEE DOI 1703
LRR: Low Rank Representation. Cameras BibRef

Hu, Y.L.[Yong-Li], Luo, C.C.[Cui-Cui], Gao, J.B.[Jun-Bin], Wang, B.Y.[Bo-Yue], Sun, Y.F.[Yan-Feng], Yin, B.C.[Bao-Cai],
Shareability-Exclusivity Representation on Product Grassmann Manifolds for Multi-camera video clustering,
JVCIR(84), 2022, pp. 103457.
Elsevier DOI 2204
Multi-camera video clustering, Grassmann manifolds, Product Grassmann manifolds BibRef

Lai, S.F.[Shao-Fan], Zheng, W.S.[Wei-Shi], Hu, J.F.[Jian-Fang], Zhang, J.G.[Jian-Guo],
Global-Local Temporal Saliency Action Prediction,
IP(27), No. 5, May 2018, pp. 2272-2285.
IEEE DOI 1804
Action from partial observation. Sequence as a whole and individual parts. feature extraction, image motion analysis, image sequences, learning (artificial intelligence), video signal processing, gapfilling BibRef

Qin, Z.[Zhen], Shelton, C.R.[Christian R.],
Event Detection in Continuous Video: An Inference in Point Process Approach,
IP(26), No. 12, December 2017, pp. 5680-5691.
IEEE DOI 1710
high-level semantic events, Inference algorithms, Semantics, BibRef

Wu, C.X.[Chen-Xia], Zhang, J.[Jiemi], Sener, O., Selman, B., Savarese, S.[Silvio], Saxena, A.[Ashutosh],
Watch-n-Patch: Unsupervised Learning of Actions and Relations,
PAMI(40), No. 2, February 2018, pp. 467-481.
IEEE DOI 1801
BibRef
Earlier: A1, A2, A5, A6, Only:
Watch-n-patch: Unsupervised understanding of actions and relations,
CVPR15(4362-4370)
IEEE DOI 1510
Bayes methods, Dairy products, Hidden Markov models, Microwave FETs, Robots, Skeleton, robot application BibRef

Georgakis, C.[Christos], Panagakis, Y.[Yannis], Pantic, M.[Maja],
Dynamic Behavior Analysis via Structured Rank Minimization,
IJCV(126), No. 2-4, April 2018, pp. 333-357.
Springer DOI 1804
Experiments on 3 distinct dynamic behavior analysis tasks, conflict intensity prediction, prediction of valence and arousal, and tracklet matching. BibRef

Akhtar, Z., Falk, T.H.,
Visual Nonverbal Behavior Analysis: The Path Forward,
MultMedMag(25), No. 2, April 2018, pp. 47-60.
IEEE DOI 1808
Visualization, Signal processing, Multimedia communication, Social factors, Human computer interaction, multimedia, multimodal BibRef

Jordao, A.[Artur], Torres, L.A.B.[Leonardo Antônio Borges], Schwartz, W.R.[William Robson],
Novel approaches to human activity recognition based on accelerometer data,
SIViP(12), No. 7, October 2018, pp. 1387-1394.
Springer DOI 1809
BibRef

Igor, L.O.B.[L.O. Bastos], de Melo, V.H.C.[Victor H.C.], Schwartz, W.R.[William Robson],
Bubblenet: A Disperse Recurrent Structure To Recognize Activities,
ICIP20(2216-2220)
IEEE DOI 2011
Videos, Activity recognition, Feature extraction, Employment, Dispersed recurrent layer BibRef

Naqvi, S.M.A.[Syed Moeen Ali], Yoon, M.[Myung_Keun],
Finding Widespread Events with Simple Bitmaps,
IEICE(E101-D), No. 12, December 2018, pp. 3246-3248.
WWW Link. 1812
BibRef

Marfil, R.[Rebeca], Dias, J.[Jorge], Bandera, A.[Antonio], Azzopardi, G.[George],
Cooperative and Social Robots: Understanding Human Activities and Intentions,
PRL(118), 2019, pp. 1-2.
Elsevier DOI 1902
BibRef

Menda, K.[Kunal], Chen, Y.C.[Yi-Chun], Grana, J.[Justin], Bono, J.W.[James W.], Tracey, B.D.[Brendan D.], Kochenderfer, M.J.[Mykel J.], Wolpert, D.[David],
Deep Reinforcement Learning for Event-Driven Multi-Agent Decision Processes,
ITS(20), No. 4, April 2019, pp. 1259-1268.
IEEE DOI 1904
Aerospace electronics, Aircraft, Learning (artificial intelligence), Computational modeling, multi-agent systems BibRef

Ren, Z.[Zheng], Jiang, B.[Bin], Seipel, S.[Stefan],
Capturing and Characterizing Human Activities Using Building Locations in America,
IJGI(8), No. 5, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Jelodar, A.B., Paulius, D., Sun, Y.,
Long Activity Video Understanding Using Functional Object-Oriented Network,
MultMed(21), No. 7, July 2019, pp. 1813-1824.
IEEE DOI 1906
Knowledge representation, Knowledge based systems, Object oriented modeling, Activity recognition, Pipelines, video knowledge representation BibRef

Wei, Y.W.[Yin-Wei], Wang, X.[Xiang], Guan, W.L.[Wei-Li], Nie, L.Q.[Li-Qiang], Lin, Z.C.[Zhou-Chen], Chen, B.Q.[Bao-Quan],
Neural Multimodal Cooperative Learning Toward Micro-Video Understanding,
IP(29), No. 1, 2020, pp. 1-14.
IEEE DOI 1910
A few seconds of video. feature extraction, image representation, learning (artificial intelligence), video signal processing, consistency and complementarity BibRef

Liu, B.L.[Bang-Li], Cai, H.B.[Hai-Bin], Ju, Z.J.[Zhao-Jie], Liu, H.H.[Hong-Hai],
Multi-stage adaptive regression for online activity recognition,
PR(98), 2020, pp. 107053.
Elsevier DOI 1911
Online activity recognition, Interaction recognition, Partial observation, Adaptive regression BibRef

Li, C.L.[Chang-Lin], Li, Z.H.[Zhi-Hui], Ge, Z.Y.[Zong-Yuan], Li, M.J.[Ming-Jie],
Knowledge driven temporal activity localization,
JVCIR(64), 2019, pp. 102628.
Elsevier DOI 1911
Temporal activity detection, Knowledge constraints, Reasoning module BibRef

Vishwakarma, D.K.[Dinesh Kumar], Dhiman, C.[Chhavi],
A unified model for human activity recognition using spatial distribution of gradients and difference of Gaussian kernel,
VC(35), No. 11, November 2018, pp. 1595-1613.
WWW Link. 1911
BibRef

Zunino, A.[Andrea], Cavazza, J.[Jacopo], Volpi, R.[Riccardo], Morerio, P.[Pietro], Cavallo, A.[Andrea], Becchio, C.[Cristina], Murino, V.[Vittorio],
Predicting Intentions from Motion: The Subject-Adversarial Adaptation Approach,
IJCV(128), No. 1, January 2020, pp. 220-239.
Springer DOI 2002
What will happen next. BibRef

Zunino, A.[Andrea], Cavazza, J.[Jacopo], Koul, A.[Atesh], Cavallo, A.[Andrea], Becchio, C.[Cristina], Murino, V.[Vittorio],
What Will I Do Next? The Intention from Motion Experiment,
Cognition17(1-8)
IEEE DOI 1709
Activity recognition, Ear, Grasping, Kinematics, Videos BibRef

Zunino, A.[Andrea], Cavazza, J.[Jacopo], Murino, V.[Vittorio],
Revisiting Human Action Recognition: Personalization vs. Generalization,
CIAP17(I:469-480).
Springer DOI 1711
BibRef

Gammulle, H.[Harshala], Denman, S.[Simon], Sridharan, S.[Sridha], Fookes, C.[Clinton],
Fine-grained action segmentation using the semi-supervised action GAN,
PR(98), 2020, pp. 107039.
Elsevier DOI 1911
Human action segmentation, Generative adversarial networks, Context modelling BibRef

Gammulle, H.[Harshala], Fernando, T.[Tharindu], Denman, S.[Simon], Sridharan, S.[Sridha], Fookes, C.[Clinton],
Coupled Generative Adversarial Network for Continuous Fine-Grained Action Segmentation,
WACV19(200-209)
IEEE DOI 1904
BibRef
Earlier: A2, A3, A4, A5, Only:
Task Specific Visual Saliency Prediction with Memory Augmented Conditional Generative Adversarial Networks,
WACV18(1539-1548)
IEEE DOI 1806
feature extraction, image recognition, image representation, image segmentation, image sequences, Couplings. image classification, image representation, learning (artificial intelligence), Visualization. BibRef

Gammulle, H.[Harshala], Denman, S.[Simon], Sridharan, S.[Sridha], Fookes, C.[Clinton],
Hierarchical Attention Network for Action Segmentation,
PRL(131), 2020, pp. 442-448.
Elsevier DOI 2004
BibRef
And:
Multi-level Sequence GAN for Group Activity Recognition,
ACCV18(I:331-346).
Springer DOI 1906
BibRef
And:
Two Stream LSTM: A Deep Fusion Framework for Human Action Recognition,
WACV17(177-186)
IEEE DOI 1609
Databases, Feature extraction, Neural networks, Support vector machines, Training, Video, sequences
See also Hessian-Based Affine Adaptation of Salient Local Image Features.
See also Efficient and Robust System for Multiperson Event Detection in Real-World Indoor Surveillance Scenes, An. BibRef

Gammulle, H.[Harshala], Denman, S.[Simon], Sridharan, S.[Sridha], Fookes, C.[Clinton],
Predicting the Future: A Jointly Learnt Model for Action Anticipation,
ICCV19(5561-5570)
IEEE DOI 2004
feature extraction, image motion analysis, image representation, learning (artificial intelligence), Generative adversarial networks BibRef

Umakanthan, S.[Sabanadesan], Denman, S.[Simon], Fookes, C.[Clinton], Sridharan, S.[Sridha],
Class-specific sparse codes for representing activities,
ICIP15(4902-4906)
IEEE DOI 1512
Activity representation; bag-of-words; sparse codes BibRef

Zhang, J., Shen, F., Xu, X., Shen, H.T.,
Temporal Reasoning Graph for Activity Recognition,
IP(29), 2020, pp. 5491-5506.
IEEE DOI 2005
Feature extraction, Activity recognition, Convolution, Semantics, Video sequences, temporal reasoning, activity recognition BibRef

Dang, L.M.[L. Minh], Min, K.[Kyungbok], Wang, H.X.[Han-Xiang], Piran, M.J.[M. Jalil], Lee, C.H.[Cheol Hee], Moon, H.[Hyeonjoon],
Sensor-based and vision-based human activity recognition: A comprehensive survey,
PR(108), 2020, pp. 107561.
Elsevier DOI 2008
Human activity recognition, Action recognition, Sensors, Vision, Human-centric sensing, Deep learning, Context-awareness BibRef

Riahi, M.[Mohammadreza], Eslami, M.[Mohammad], Safavi, S.H.[Seyed Hamid], Torkamani-Azar, F.[Farah],
Human activity recognition using improved dynamic image,
IET-IPR(14), No. 13, November 2020, pp. 3223-3231.
DOI Link 2012
Get the action information from the first few frames. BibRef

Liu, X.L.[Xiao-Li], Li, Z.B.[Zhi-Bin],
Deeply fusing multi-model quality-aware features for sophisticated human activity understanding,
SP:IC(84), 2020, pp. 115809.
Elsevier DOI 2004
Human action recognition, Image quality correlation, Multi-channel feature fusion, Video retrieval BibRef

Sikder, N.[Niloy], Nahid, A.A.[Abdullah-Al],
KU-HAR: An open dataset for heterogeneous human activity recognition,
PRL(146), 2021, pp. 46-54.
Elsevier DOI 2105
BibRef

Zhao, J., Deng, F., He, H., Chen, J.,
Local Domain Adaptation for Cross-Domain Activity Recognition,
HMS(51), No. 1, February 2021, pp. 12-21.
IEEE DOI 2101
Legged locomotion, Activity recognition, Training, Sensors, Gyroscopes, Computational modeling, Ubiquitous computing, wearable sensor BibRef

Wei, Z.J.[Zi-Jun], Wang, B.Y.[Bo-Yu], Hoai, M.[Minh], Zhang, J.M.[Jian-Ming], Shen, X.H.[Xiao-Hui], Lin, Z.[Zhe], Mech, R.[Radomír], Samaras, D.[Dimitris],
Sequence-to-Segments Networks for Detecting Segments in Videos,
PAMI(43), No. 3, March 2021, pp. 1009-1021.
IEEE DOI 2102
Videos, Proposals, Decoding, Time series analysis, Task analysis, Segment detection, video temporal action proposal BibRef

Sun, Y.[Yan], Hare, J.S.[Jonathon S.], Nixon, M.S.[Mark S.],
On parameterizing higher-order motion for behaviour recognition,
PR(112), 2021, pp. 107710.
Elsevier DOI 2102
Motion analysis, Higher-order motion, Acceleration, Jerk, Snap BibRef

Synakowski, S.[Stuart], Feng, Q.L.[Qian-Li], Martinez, A.[Aleix],
Adding Knowledge to Unsupervised Algorithms for the Recognition of Intent,
IJCV(129), No. 4, April 2021, pp. 942-959.
Springer DOI 2104
Was the action intentional? BibRef

Nath, C.D.[Chayanika D.], Hazarika, S.M.[Shyamanta M.],
Activity recognition in video sequences over qualitative abstracts of a diagram-based representation schema,
JVCIR(76), 2021, pp. 103061.
Elsevier DOI 2104
Cognitive vision, Video analysis, Activity recognition, Qualitative spatial and temporal reasoning, Diagrammatic reasoning BibRef

Kasnesis, P.[Panagiotis], Chatzigeorgiou, C.[Christos], Patrikakis, C.Z.[Charalampos Z.], Rangoussi, M.[Maria],
Modality-wise relational reasoning for one-shot sensor-based activity recognition,
PRL(146), 2021, pp. 90-99.
Elsevier DOI 2105
Deep learning, One-shot learning, Human activity recognition, Relational reasoning, Self-attention BibRef

Psaltis, A.[Athanasios], Patrikakis, C.Z.[Charalampos Z.], Daras, P.[Petros],
Deep Multi-modal Representation Schemes for Federated 3d Human Action Recognition,
DSC22(334-352).
Springer DOI 2304
BibRef

Kumaran, N.[Natarajan], Reddy, U.S.[Uyyala Srinivasulu],
Classification of human activity detection based on an intelligent regression model in video sequences,
IET-IPR(15), No. 1, 2021, pp. 65-76.
DOI Link 2106
BibRef

Li, W.Q.[Wei-Qi], Wang, J.M.[Jian-Ming], Liang, J.Y.[Jia-Yu], Jin, G.H.[Guang-Hao], Chung, T.S.[Tae-Sun],
Online dense activity detection,
IET-CV(15), No. 5, 2021, pp. 323-333.
DOI Link 2107
BibRef

Gu, F.Q.[Fu-Qiang], Chung, M.H.[Mu-Huan], Chignell, M.[Mark], Valaee, S.[Shahrokh], Zhou, B.D.[Bao-Ding], Liu, X.[Xue],
A Survey on Deep Learning for Human Activity Recognition,
Surveys(54), No. 8, October 2021, pp. xx-yy.
DOI Link 2110
Survey, Human Activity. deep models, deep learning, Machine learning, mobile sensing, activity recognition BibRef

Kahatapitiya, K.[Kumara], Ryoo, M.S.[Michael S.],
Coarse-Fine Networks for Temporal Activity Detection in Videos,
CVPR21(8381-8390)
IEEE DOI 2111
Location awareness, Codes, Fuses, Dynamics, Feature extraction BibRef

Chen, L.F.[Li-Fei], Wu, H.Y.[Hai-Yan], Kang, W.X.[Wen-Xuan], Wang, S.R.[Sheng-Rui],
Symbolic sequence representation with Markovian state optimization,
PR(131), 2022, pp. 108849.
Elsevier DOI 2208
Sequence representation, Hidden Markov model, State clustering, Hierarchical model selection, Activity recognition BibRef

Yu, W.J.[Wei-Jiang], Wang, H.F.[Hao-Fan], Li, G.H.[Guo-Hao], Xiao, N.[Nong], Ghanem, B.[Bernard],
Knowledge-Aware Global Reasoning for Situation Recognition,
PAMI(45), No. 7, July 2023, pp. 8621-8633.
IEEE DOI 2306
activity happening (salient action) in an image and the nouns of all associated semantic roles playing in the activity. Cognition, Task analysis, Visualization, Correlation, Semantics, Nanoelectromechanical systems, Image edge detection, situation recognition BibRef

Heilbron, F.C.[Fabian Caba], Escorcia, V.[Victor], Ghanem, B.[Bernard], Niebles, J.C.[Juan Carlos],
ActivityNet: A large-scale video benchmark for human activity understanding,
CVPR15(961-970)
IEEE DOI 1510
BibRef

Bourbakis, N.[Nikolaos], Angeleas, A.[Anargyros],
A Synergistic Formal-Statistical Model for Recognizing Complex Human Activities,
HMS(54), No. 3, June 2024, pp. 229-237.
IEEE DOI 2405
Foot, Symbols, Image segmentation, Grammar, Reviews, Legged locomotion, Turning, Complex activity, human activity recognition, human pose estimation BibRef

Jung, G.[Gyuwon], Park, S.[Sangjun], Ma, E.Y.[Eun-Yeol], Kim, H.[Heeyoung], Lee, U.[Uichin],
Tutorial on Matching-based Causal Analysis of Human Behaviors Using Smartphone Sensor Data,
Surveys(56), No. 9, April 2024, pp. 236.
DOI Link 2405
Smartphone sensor data, causal inference, human behavior, observational study BibRef

Yang, X.S.[Xiao-Shan], Xiong, B.C.[Bao-Chen], Huang, Y.[Yi], Xu, C.S.[Chang-Sheng],
Cross-Modal Federated Human Activity Recognition,
PAMI(46), No. 8, August 2024, pp. 5345-5361.
IEEE DOI 2407
Human activity recognition, Task analysis, Videos, Data models, Servers, Federated learning, Feature extraction, human activity recognition BibRef

Ye, X.Z.[Xiao-Zhou], Wang, K.I.K.[Kevin I-Kai],
Deep generative domain adaptation with temporal relation attention mechanism for cross-user activity recognition,
PR(156), 2024, pp. 110811.
Elsevier DOI 2408
Human activity recognition, Deep domain adaptation, Data out-of-distribution, Temporal relation knowledge, Time series classification BibRef

Tang, Y.[Yutao], Béjar, B.[Benjamín], Vidal, R.[René],
Semantic-aware Video Representation for Few-shot Action Recognition,
WACV24(6444-6454)
IEEE DOI 2404
Adaptation models, Visualization, Solid modeling, Fuses, Semantics, Algorithms, Video recognition and understanding, Algorithms, Vision + language and/or other modalities BibRef

Djenouri, Y.[Youcef], Belbachir, A.N.[Ahmed Nabil],
A Hybrid Visual Transformer for Efficient Deep Human Activity Recognition,
NIVT23(721-730)
IEEE DOI 2401
BibRef

Lu, A.[Andrew], Lin, X.D.[Xu-Dong], Niu, Y.[Yulei], Chang, S.F.[Shih-Fu],
In Defense of Structural Symbolic Representation for Video Event-Relation Prediction,
L3D-IVU23(4940-4950)
IEEE DOI 2309
BibRef

Tang, Y.S.[Yan-Song], Liu, J.P.[Jin-Peng], Liu, A.[Aoyang], Yang, B.[Bin], Dai, W.X.[Wen-Xun], Rao, Y.M.[Yong-Ming], Lu, J.W.[Ji-Wen], Zhou, J.[Jie], Li, X.[Xiu],
FLAG3D: A 3D Fitness Activity Dataset with Language Instruction,
CVPR23(22106-22117)
IEEE DOI 2309
BibRef

Wang, S.Z.[Sheng-Zhi], Xiao, S.[Shuo], Wang, Y.[Yu], Jiang, H.F.[Hai-Feng], Zhang, G.[Guopeng],
A Deep Dilated Convolutional Self-attention Model for Multimodal Human Activity Recognition,
ICPR22(791-797)
IEEE DOI 2212
Deep learning, Convolution, Multimodal sensors, Benchmark testing, Feature extraction, Ubiquitous computing, Human activity recognition BibRef

Qian, Y.C.[Yi-Cheng], Luo, W.X.[Wei-Xin], Lian, D.Z.[Dong-Ze], Tang, X.[Xu], Zhao, P.L.[Pei-Lin], Gao, S.H.[Sheng-Hua],
SVIP: Sequence VerIfication for Procedures in Videos,
CVPR22(19858-19870)
IEEE DOI 2210
Measurement, Codes, Annotations, Transformers, Character recognition, Task analysis, Action and event recognition, Video analysis and understanding BibRef

Liu, C.H.[Chun-Hui], Li, X.Y.[Xin-Yu], Chen, H.[Hao], Modolo, D.[Davide], Tighe, J.[Joseph],
Selective Feature Compression for Efficient Activity Recognition Inference,
ICCV21(13608-13617)
IEEE DOI 2203
Computational modeling, Crops, Activity recognition, Task analysis, Kernel, Videos, Action and behavior recognition, Video analysis and understanding BibRef

Sayed, S.[Saif], Athitsos, V.[Vassilis],
Cross Your Body: a Cognitive Assessment System for Children,
ISVC21(II:97-109).
Springer DOI 2112
BibRef

Zhang, Y.Y.[Yan-Yi], Li, X.Y.[Xin-Yu], Marsic, I.[Ivan],
Multi-Label Activity Recognition using Activity-specific Features and Activity Correlations,
CVPR21(14620-14630)
IEEE DOI 2111
Visualization, Correlation, Codes, Activity recognition, Feature extraction BibRef

Tseng, A.[Albert], Sun, J.J.[Jennifer J.], Yue, Y.S.[Yi-Song],
Automatic Synthesis of Diverse Weak Supervision Sources for Behavior Analysis,
CVPR22(2201-2210)
IEEE DOI 2210
Training, Costs, Limiting, Annotations, Scalability, Behavioral sciences, Pattern recognition, Behavior analysis BibRef

Sun, J.J.[Jennifer J.], Kennedy, A.[Ann], Zhan, E.[Eric], Anderson, D.J.[David J.], Yue, Y.S.[Yi-Song], Perona, P.[Pietro],
Task Programming: Learning Data Efficient Behavior Representations,
CVPR21(2875-2884)
IEEE DOI 2111
Training, Video tracking, Annotations, Programming, Tools, Mice, Trajectory BibRef

Ben-Shabat, Y.Z.[Yi-Zhak], Yu, X.[Xin], Saleh, F.[Fatemeh], Campbell, D.[Dylan], Rodriguez-Opazo, C.[Cristian], Li, H.D.[Hong-Dong], Gould, S.[Stephen],
The IKEA ASM Dataset: Understanding People Assembling Furniture through Actions, Objects and Pose,
WACV21(846-858)
IEEE DOI
WWW Link. 2106
Dataset, Activity Recognition. Deep learning, Annotations, Pose estimation, Object segmentation, Benchmark testing BibRef

Corona, K.[Kellie], Osterdahl, K.[Katie], Collins, R.[Roderic], Hoogs, A.J.[Anthony J.],
MEVA: A Large-Scale Multiview, Multimodal Video Dataset for Activity Detection,
WACV21(1059-1067)
IEEE DOI 2106
Dataset, Activity Detection. Solid modeling, Visualization, Annotations, NIST, Cameras
See also Multiview Extended Video with Activities. BibRef

Godil, A.[Afzal], Lee, Y.Y.[Yoo-Young], Fiscus, J.[Jon], Delgado, A.[Andrew], Godard, E.[Eliot], Chocot, B.[Baptiste], Diduch, L.[Lukas], Golden, J.[Jim], Zhang, J.[Jesse],
2020 Sequestered Data Evaluation for Known Activities in Extended Video: Summary and Results,
WACVW21(51-59) Activity Detection
IEEE DOI 2105
Measurement, System performance, NIST, Safety, Task analysis BibRef

Zhang, C.Y.[Chen-Yang], Tian, Z.Q.[Zhi-Qiang], Song, J.Y.[Jing-Yi], Zheng, Y.Y.[Yao-Yue], Xu, B.[Bo],
Construction worker hardhat-wearing detection based on an improved BiFPN,
ICPR21(8600-8607)
IEEE DOI 2105
Training, Personal protective equipment, Deep learning, Fuses, Semantics, Production, Object detection BibRef

Tang, H.[Haowen], Wei, P.[Ping], Li, H.[Huan], Zheng, N.N.[Nan-Ning],
Inferring Tasks and Fluents in Videos by Learning Causal Relations,
ICPR21(7566-7572)
IEEE DOI 2105
Support vector machines, Collaboration, Search problems, Task analysis, Videos BibRef

Qasim, T.[Tehreem], Fisher, R.B.[Robert B.], Bhatti, N.[Naeem],
Ground-truthing Large Human Behavior Monitoring Datasets,
ICPR21(2763-2770)
IEEE DOI 2105
Image analysis, Video sequences, Manuals, Pattern recognition, Labeling, Convolutional neural networks, Task analysis BibRef

Hosono, T.[Takashi], Sawada, K.[Kiyohito], Sun, Y.Q.[Yong-Qing], Hayase, K.[Kazuya], Shimamura, J.[Jun],
Activity Normalization for Activity Detection in Surveillance Videos,
ICIP20(1386-1390)
IEEE DOI 2011
Proposals, Videos, Automobiles, Surveillance, Histograms, Cameras, Object detection, Activity detection, surveillance videos, data normalization BibRef

Chen, S.X.[Shao-Xiang], Jiang, W.H.[Wen-Hao], Liu, W.[Wei], Jiang, Y.G.[Yu-Gang],
Learning Modality Interaction for Temporal Sentence Localization and Event Captioning in Videos,
ECCV20(IV:333-351).
Springer DOI 2011
BibRef

Zhao, H.[He], Wildes, R.P.[Richard P.],
On Diverse Asynchronous Activity Anticipation,
ECCV20(XXIX: 781-799).
Springer DOI 2010
BibRef

Cruz, R.S., Cherian, A., Fernando, B., Campbell, D., Gould, S.,
Inferring Temporal Compositions of Actions Using Probabilistic Automata,
CICV20(1514-1522)
IEEE DOI 2008
Videos, Probabilistic logic, Task analysis, Automata, Pattern recognition, Natural languages, Training data BibRef

Li, Y., Xu, L., Liu, X., Huang, X., Xu, Y., Wang, S., Fang, H., Ma, Z., Chen, M., Lu, C.,
PaStaNet: Toward Human Activity Knowledge Engine,
CVPR20(379-388)
IEEE DOI 2008
Semantics, Head, Feature extraction, Engines, Knowledge based systems, Task analysis, Crowdsourcing BibRef

Jaiswal, M.[Mayoore], Liu, F.[Frank], Jagannathan, A.[Anupama], Gattiker, A.[Anne], Hwang, I.[Inseok], Lee, J.H.[Jin-Ho], Tong, M.[Matthew], Dureja, S.[Sahil], Shah, S.[Soham], Hofstee, P.[Peter], Chen, V.[Valerie], Paul, S.[Suvadip], Feris, R.S.[Rogerio S.],
Video-Text Compliance: Activity Verification Based on Natural Language Instructions,
HVU19(1503-1512)
IEEE DOI 2004
Does the action correspond to the text description. data privacy, gesture recognition, natural language processing, text analysis, video signal processing, auto augmentation BibRef

Zhai, Y.H.[Yuan-Hao], Liu, Z.[Ziyi], Wu, Z.Y.[Zhen-Yu], Wu, Y.[Yi], Zhou, C.L.[Chun-Luan], Doermann, D.[David], Yuan, J.S.[Jun-Song], Hua, G.[Gang],
SOAR: Scene-debiasing Open-set Action Recognition,
ICCV23(10210-10220)
IEEE DOI 2401
BibRef

Yu, T.[Tan], Ren, Z.[Zhou], Li, Y.C.[Yun-Cheng], Yan, E.X.[En-Xu], Xu, N.[Ning], Yuan, J.S.[Jun-Song],
Temporal Structure Mining for Weakly Supervised Action Detection,
ICCV19(5521-5530)
IEEE DOI 2004
Consider the whole sequence and the relation of sequential actions. data mining, image segmentation, video signal processing, weakly supervised action detection, Visualization BibRef

Zhu, X.Q.[Xin-Qi], Xu, C.[Chang], Hui, L.W.[Lang-Wen], Lu, C.W.[Ce-Wu], Tao, D.C.[Da-Cheng],
Approximated Bilinear Modules for Temporal Modeling,
ICCV19(3493-3502)
IEEE DOI 2004
Code, Convolutional Neural Networks.
WWW Link. Fine-grained models. convolutional neural nets, feature extraction, image classification, image representation, inference mechanisms, Image recognition BibRef

Baptista-Ríos, M., López-Sastre, R.J., Caba-Heilbron, F., van Gemert, J.C., Acevedo-Rodríguez, F.J., Maldonado-Bascón, S.,
The Instantaneous Accuracy: a Novel Metric for the Problem of Online Human Behaviour Recognition in Untrimmed Videos,
HBU19(1282-1284)
IEEE DOI 2004
behavioural sciences computing, object detection, object recognition, video signal processing, untrimmed videos BibRef

Yao, L.[Li], Qian, Y.[Ying],
Novel Activities Detection Algorithm in Extended Videos,
HADCV19(9-15)
IEEE DOI 1902
Videos, Target tracking, Object detection, Object tracking, Feature extraction BibRef

Thomanek, R.[Rico], Roschke, C.[Christian], Platte, B.[Benny], Manthey, R.[Robert], Rolletschke, T.[Tony], Heinzig, M.[Manuel], Vodel, M.[Matthias], Zimmer, F.[Frank], Eibl, M.[Maximilian],
A Scalable System Architecture for Activity Detection with Simple Heuristics,
HADCV19(27-34)
IEEE DOI 1902
Streaming media, Tracking, Task analysis, Object detection, Distributed databases, Cameras BibRef

Zhang, C.[Can], Zou, Y.X.[Yue-Xian], Chen, G.[Guang],
Hierarchical Temporal Pooling for Efficient Online Action Recognition,
MMMod19(I:471-482).
Springer DOI 1901
BibRef

Chen, G.[Guang], Zou, Y.X.[Yue-Xian], Zhang, C.[Can],
STMP: Spatial Temporal Multi-level Proposal Network for Activity Detection,
MMMod19(I:29-41).
Springer DOI 1901
BibRef

Bhattacharyya, A.[Apratim], Schiele, B.[Bernt], Fritz, M.[Mario],
Accurate and Diverse Sampling of Sequences Based on a 'Best of Many' Sample Objective,
CVPR18(8485-8493)
IEEE DOI 1812
Predictive models, Training, Task analysis, Trajectory, Image sequences, Data models, Recurrent neural networks BibRef

Cherian, A.[Anoop], Sra, S.[Suvrit], Gould, S.[Stephen], Hartley, R.I.[Richard I.],
Non-linear Temporal Subspace Representations for Activity Recognition,
CVPR18(2197-2206)
IEEE DOI 1812
Kernel, Hilbert space, Manifolds, Principal component analysis, Optimization, Feature extraction BibRef

Paul, S.[Sujoy], Roy, S.[Sourya], Roy-Chowdhury, A.K.[Amit K.],
W-TALC: Weakly-Supervised Temporal Activity Localization and Classification,
ECCV18(II: 588-607).
Springer DOI 1810
BibRef

Käse, N., Babaee, M., Rigoll, G.,
Multi-view human activity recognition using motion frequency,
ICIP17(3963-3967)
IEEE DOI 1803
Activity recognition, Cameras, Databases, Feature extraction, motion frequency BibRef

Dai, X.Y.[Xi-Yang], Singh, B.[Bharat], Ng, J.Y.H.[Joe Yue-Hei], Davis, L.S.[Larry S.],
TAN: Temporal Aggregation Network for Dense Multi-Label Action Recognition,
WACV19(151-160)
IEEE DOI 1904
convolution, feature extraction, image recognition, image representation, TAN, dense multilabel action recognition, Stacking
See also FASON: First and Second Order Information Fusion Network for Texture Recognition. BibRef

Dai, X.Y.[Xi-Yang], Singh, B.[Bharat], Zhang, G., Davis, L.S.[Larry S.], Chen, Y.Q.,
Temporal Context Network for Activity Localization in Videos,
ICCV17(5727-5736)
IEEE DOI 1802
convolution, feature extraction, gesture recognition, image classification, image motion analysis, Videos BibRef

Xu, M.Z.[Ming-Ze], Fan, C.Y.[Chen-You], Wang, Y.C.[Yu-Chen], Ryoo, M.S.[Michael S.], Crandall, D.J.[David J.],
Joint Person Segmentation and Identification in Synchronized First- and Third-Person Videos,
ECCV18(I: 656-672).
Springer DOI 1810
BibRef

Fan, C.Y.[Chen-You], Lee, J.[Jangwon], Xu, M.Z.[Ming-Ze], Singh, K.K.[Krishna Kumar], Lee, Y.J.[Yong Jae], Crandall, D.J.[David J.], Ryoo, M.S.[Michael S.],
Identifying First-Person Camera Wearers in Third-Person Videos,
CVPR17(4734-4742)
IEEE DOI 1711
Activity recognition, Cameras, Network architecture, Trajectory, Videos, Visualization BibRef

Cherian, A.[Anoop], Fernando, B., Harandi, M., Gould, S.[Stephen],
Generalized Rank Pooling for Activity Recognition,
CVPR17(1581-1590)
IEEE DOI 1711
Activity recognition, Computational modeling, Integrated circuit modeling, Manifolds, Optimization, Standards, Video, sequences BibRef

Ho, S.B.[Seng-Beng],
The Role of Synchronic Causal Conditions in Visual Knowledge Learning,
Cognition17(9-16)
IEEE DOI 1709
Correlation, Encoding, Problem-solving, Psychology, Visualization, Weapons BibRef

Lei, J.[Jun], Li, G.H.[Guo-Hui], Zhang, J.[Jun], Li, S.H.[Shuo-Hao], Wang, F.L.[Feng-Lei],
Continuous action recognition with weakly labelling videos,
MVA17(242-245)
DOI Link 1708
Feature extraction, Labeling, Organizations, Supervised learning, Training, Videos, Visualization. Order of action labels, not location. BibRef

Kataoka, H.[Hirokatsu], Miyashita, Y.[Yudai], Hayashi, M.[Masaki], Iwata, K.[Kenji], Satoh, Y.[Yutaka],
Recognition of Transitional Action for Short-Term Action Prediction using Discriminative Temporal CNN Feature,
BMVC16(xx-yy).
HTML Version. 1805
BibRef

Khelalef, A.[Aziz], Ababsa, F.[Fakhreddine], Benoudjit, N.[Nabil],
A Simple Human Activity Recognition Technique Using DCT,
ACIVS16(37-46).
Springer DOI 1611
BibRef

Kataoka, H.[Hirokatsu], Iwata, K.[Kenji], Satoh, Y.[Yutaka], Hayashi, M., Aoki, Y.[Yoshimitsu], Ilic, S.[Slobodan],
Dominant Codewords Selection with Topic Model for Action Recognition,
ChaLearn16(770-777)
IEEE DOI 1612
BibRef

Hasan, M.[Mahmudul], Choi, J.H.[Jong-Hyun], Neumann, J.[Jan], Roy-Chowdhury, A.K.[Amit K.], Davis, L.S.[Larry S.],
Learning Temporal Regularity in Video Sequences,
CVPR16(733-742)
IEEE DOI 1612
BibRef

Su, Y.C.[Yu-Chuan], Grauman, K.[Kristen],
Leaving Some Stones Unturned: Dynamic Feature Prioritization for Activity Detection in Streaming Video,
ECCV16(VII: 783-800).
Springer DOI 1611
BibRef

Watagawa, M., Shinoda, T., Hasegawa, K.,
Estimating The Amount Of Ship Recycling Activity Using Remote Sensing Application,
ISPRS16(B8: 1195-1200).
DOI Link 1610
BibRef

Yan, W.Q.[Wei Qi], Liu, F.[Feng],
Event Analogy Based Privacy Preservation in Visual Surveillance,
VSWS15(357-368).
Springer DOI 1603
BibRef

Timofte, R.[Radu], Rothe, R., Van Gool, L.J.,
Seven Ways to Improve Example-Based Single Image Super Resolution,
CVPR16(1865-1873)
IEEE DOI 1612
BibRef

Rothe, R., Timofte, R.[Radu], Van Gool, L.J.[Luc J.],
DLDR: Deep Linear Discriminative Retrieval for Cultural Event Classification from a Single Image,
ChaLearnDec15(295-302)
IEEE DOI 1602
Agriculture BibRef

Liu, M., Liu, X., Li, Y., Chen, X., Hauptmann, A.G., Shan, S.,
Exploiting Feature Hierarchies with Convolutional Neural Networks for Cultural Event Recognition,
ChaLearnDec15(274-279)
IEEE DOI 1602
Cultural differences BibRef

Wei, X.S., Gao, B.B., Wu, J.,
Deep Spatial Pyramid Ensemble for Cultural Event Recognition,
ChaLearnDec15(280-286)
IEEE DOI 1602
Cultural differences BibRef

Wu, T., Gurram, P., Rao, R.M., Bajwa, W.U.,
Clustering-aware structure-constrained low-rank representation model for learning human action attributes,
IVMSP16(1-5)
IEEE DOI 1608
BibRef
Earlier:
Hierarchical Union-of-Subspaces Model for Human Activity Summarization,
VidSum15(1053-1061)
IEEE DOI 1602
Clustering algorithms BibRef

Batabyal, T.[Tamal], Acton, S.T.[Scott T.], Vaccari, A.[Andrea],
UGrAD: A graph-theoretic framework for classification of activity with complementary graph boundary detection,
ICIP16(1339-1343)
IEEE DOI 1610
Bipartite graph BibRef
Earlier: A1, A3, A2:
LaWeCo: Active region detection in non-uniformly sampled data using Laplacian-weighted covariance,
Southwest16(129-132)
IEEE DOI 1605
BibRef
And: A1, A3, A2:
UGraSP: A unified framework for activity recognition and person identification using graph signal processing,
ICIP15(3270-3274)
IEEE DOI 1512
Covariance matrices. Adjacency Matrix BibRef

Avgerinakis, K.[Konstantinos], Adam, K.[Katerina], Briassouli, A.[Alexia], Kompatsiaris, Y.F.[Yi-Fannis],
Moving camera human activity localization and recognition with motionplanes and multiple homographies,
ICIP15(2085-2089)
IEEE DOI 1512
activity localization; activity recognition; homography; motionplanes BibRef

Stephens, K., Bors, A.G.,
Human group activity recognition based on modelling moving regions interdependencies,
ICPR16(2115-2120)
IEEE DOI 1705
BibRef
And:
Group activity recognition on outdoor scenes,
AVSS16(59-65)
IEEE DOI 1611
BibRef
And:
Grouping multi-vector streaklines for human activity identification,
IVMSP16(1-5)
IEEE DOI 1608
BibRef
And:
Observing human activities using movement modelling,
AVSS15(1-6)
IEEE DOI 1511
Activity recognition, Cameras, Computational modeling, Estimation, Manuals, Mathematical model, Tracking, Group Activity Identification, Motion Segmentation, Streaklines. Computational modeling. Cameras. Gaussian processes BibRef

Martinel, N.[Niki], Avola, D.[Danilo], Piciarelli, C.[Claudio], Micheloni, C.[Christian], Vernier, M.[Marco], Cinque, L.[Luigi], Foresti, G.L.[Gian Luca],
Selection of Temporal Features for Event Detection in Smart Security,
CIAP15(II:609-619).
Springer DOI 1511
BibRef

Salvador, A.[Amaia], Manchon-Vizuete, D.[Daniel], Calafell, A.[Andrea], Giro-i-Nieto, X.[Xavier], Zeppelzauer, M.[Matthias],
Cultural Event recognition with visual ConvNets and temporal models,
ChaLearn15(36-44)
IEEE DOI 1510
Computational modeling BibRef

Park, S.[Sungheon], Kwak, N.[Nojun],
Cultural event recognition by subregion classification with convolutional neural network,
ChaLearn15(45-50)
IEEE DOI 1510
Accuracy BibRef

Kwon, H.[Heeyoung], Yun, K.[Kiwon], Hoai, M.[Minh], Samaras, D.[Dimitris],
Recognizing cultural events in images: A study of image categorization models,
ChaLearn15(51-57)
IEEE DOI 1510
Cultural differences BibRef

Liang, J.W.[Jing-Wei], Fadili, J.[Jalal], Peyré, G.[Gabriel], Luke, R.[Russell],
Activity Identification and Local Linear Convergence of Douglas-Rachford/ADMM under Partial Smoothness,
SSVM15(642-653).
Springer DOI 1506
BibRef

Kuehne, H.[Hilde], Arslan, A.[Ali], Serre, T.[Thomas],
The Language of Actions: Recovering the Syntax and Semantics of Goal-Directed Human Activities,
CVPR14(780-787)
IEEE DOI 1409
BibRef

Adeli-Mosabbeb, E.[Ehsan], Cabral, R.S.[Ricardo S.], de la Torre, F.[Fernando], Fathy, M.[Mahmood],
Multi-label Discriminative Weakly-Supervised Human Activity Recognition and Localization,
ACCV14(V: 241-258).
Springer DOI 1504
BibRef

Chakraborty, A.[Anirban], Roy-Chowdhury, A.K.[Amit K.],
Context-Aware Activity Forecasting,
ACCV14(V: 21-36).
Springer DOI 1504
BibRef

Killedar, D., Sasi, S.,
Human activity detection using sparse representation,
AIPR14(1-5)
IEEE DOI 1504
feature extraction BibRef

Lan, T.[Tian], Chen, L.[Lei], Deng, Z.W.[Zhi-Wei], Zhou, G.T.[Guang-Tong], Mori, G.[Greg],
Learning Action Primitives for Multi-level Video Event Understanding,
Re-Id14(95-110).
Springer DOI 1504
BibRef

Singh, B., Han, X., Wu, Z., Morariu, V.I.[Vlad I.], Davis, L.S.[Larry S.],
Selecting Relevant Web Trained Concepts for Automated Event Retrieval,
ICCV15(4561-4569)
IEEE DOI 1602
Calibration BibRef

Lee, H.T.[Hyung-Tae], Morariu, V.I.[Vlad I.], Davis, L.S.[Larry S.],
Clauselets: Leveraging Temporally Related Actions for Video Event Analysis,
WACV15(1161-1168)
IEEE DOI 1503
Sets of concurrent actions and their temporal relationships. BibRef

Khoualed, S.[Samir], Chateau, T.[Thierry], Castellan, U.[Umberto], Samir, C.[Chafik],
An augmented representation of activity in video using semantic-context information,
ICIP14(4171-4175)
IEEE DOI 1502
Accuracy BibRef

Alemdar, H.[Hande], van Kasteren, T.L., Niessen, M.E., Merentitis, A., Ersoy, C.[Cem],
A Unified Model for Human Behavior Modeling Using a Hierarchy with a Variable Number of States,
ICPR14(3804-3809)
IEEE DOI 1412
Bayes methods BibRef

Nguyen, T.[Thuong], Gupta, S.I.[Sun-Il], Venkatesh, S.[Svetha], Phung, D.Q.[Dinh Q.],
A Bayesian Nonparametric Framework for Activity Recognition Using Accelerometer Data,
ICPR14(2017-2022)
IEEE DOI 1412
Accelerometers BibRef

Hammoud, R.I.[Riad I.], Sahin, C.S.[Cem S.], Blasch, E.P.[Erik P.], Rhodes, B.J.[Bradley J.],
Multi-source Multi-modal Activity Recognition in Aerial Video Surveillance,
PBVS14(237-244)
IEEE DOI 1409
FMV exploitation BibRef

Shankar, S.[Sukrit], Badrinarayanan, V.[Vijay], Cipolla, R.[Roberto],
Part Bricolage: Flow-Assisted Part-Based Graphs for Detecting Activities in Videos,
ECCV14(VI: 586-601).
Springer DOI 1408
BibRef

Nitta, N.[Naoko], Kumihashi, Y.[Yusuke], Kato, T.[Tomochika], Babaguchi, N.[Noboru],
Real-World Event Detection Using Flickr Images,
MMMod14(II: 307-314).
Springer DOI 1405
BibRef

Hsieh, Y.H.[Yung-Huan], Hidayati, S.C.[Shintami C.], Cheng, W.H.[Wen-Huang], Hu, M.C.[Min-Chun], Hua, K.L.[Kai-Lung],
Who's the Best Charades Player? Mining Iconic Movement of Semantic Concepts,
MMMod14(I: 231-241).
Springer DOI 1405
BibRef

Zafeiriou, L.[Lazaros], Antonakos, E.[Epameinondas], Zafeiriou, S.P.[Stefanos P.], Pantic, M.[Maja],
Joint Unsupervised Deformable Spatio-Temporal Alignment of Sequences,
CVPR16(3382-3390)
IEEE DOI 1612
BibRef
Earlier:
Joint Unsupervised Face Alignment and Behaviour Analysis,
ECCV14(IV: 167-183).
Springer DOI 1408
BibRef

Zafeiriou, L.[Lazaros], Nicolaou, M.A.[Mihalis A.], Zafeiriou, S.P.[Stefanos P.], Nikitidis, S.[Symeon], Pantic, M.[Maja],
Learning Slow Features for Behaviour Analysis,
ICCV13(2840-2847)
IEEE DOI 1403
Component Analysis; Slow Feature Analysis
See also Slow Feature Analysis for Human Action Recognition.
See also Incremental Slow Feature Analysis with Indefinite Kernel for Online Temporal Video Segmentation. BibRef

Douze, M.[Matthijs], Revaud, J.[Jerome], Schmid, C.[Cordelia], Jegou, H.[Herve],
Stable Hyper-pooling and Query Expansion for Event Detection,
ICCV13(1825-1832)
IEEE DOI 1403

See also Compact Video Description for Copy Detection with Precise Temporal Alignment. BibRef

Fang, X.Y.[Xiao-Yu], Xia, Z.W.[Zi-Wei], Su, C.[Chi], Xu, T.[Teng], Tian, Y.H.[Yong-Hong], Wang, Y.W.[Yao-Wei], Huang, T.J.[Tie-Jun],
A system based on sequence learning for event detection in surveillance video,
ICIP13(3587-3591)
IEEE DOI 1402
Event detection;sequence learning;surveillance BibRef

Codella, N.C.E.[Noel C.E.], Hua, G.[Gang], Cao, L.L.[Liang-Liang], Merler, M.[Michele], Gong, L.G.[Lei-Guang], Hill, M.[Matt], Smith, J.R.[John R.],
Large-scale video event classification using dynamic temporal pyramid matching of visual semantics,
ICIP13(2877-2881)
IEEE DOI 1402
event; pyramid; semantics; temporal; video BibRef

Gopalan, R.[Raghuraman],
Joint Sparsity-Based Representation and Analysis of Unconstrained Activities,
CVPR13(2738-2745)
IEEE DOI 1309
BibRef

Gao, J., Sun, C., Yang, Z., Nevatia, R.,
TALL: Temporal Activity Localization via Language Query,
ICCV17(5277-5285)
IEEE DOI 1802
image representation, image retrieval, natural language processing, regression analysis, text analysis, Visualization BibRef

Sun, C.[Chen], Nevatia, R.[Ram],
DISCOVER: Discovering Important Segments for Classification of Video Events and Recounting,
CVPR14(2569-2576)
IEEE DOI 1409
BibRef
Earlier:
Semantic Aware Video Transcription Using Random Forest Classifiers,
ECCV14(I: 772-786).
Springer DOI 1408
BibRef
Earlier:
ACTIVE: Activity Concept Transitions in Video Event Classification,
ICCV13(913-920)
IEEE DOI 1403
BibRef
And:
Large-scale web video event classification by use of Fisher Vectors,
WACV13(15-22).
IEEE DOI 1303
event classification; event recounting; latent svm BibRef

Sun, Q.R.[Qian-Ru], Liu, H.[Hong],
Inferring Ongoing Human Activities Based on Recurrent Self-Organizing Map Trajectory,
BMVC13(xx-yy).
DOI Link 1402
BibRef
Earlier:
Action Disambiguation Analysis Using Normalized Google-Like Distance Correlogram,
ACCV12(III:425-437).
Springer DOI 1304
BibRef

Xu, Z.[Zhen], Qing, L.Y.[Lai-Yun], Miao, J.[Jun],
Activity Auto-Completion: Predicting Human Activities from Partial Videos,
ICCV15(3191-3199)
IEEE DOI 1602
Detectors BibRef

Meng, L.X.[Ling-Xun], Qing, L.Y.[Lai-Yun], Yang, P.[Peng], Miao, J.[Jun], Chen, X.L.[Xi-Lin], Metaxas, D.N.[Dimitris N.],
Activity recognition based on semantic spatial relation,
ICPR12(609-612).
WWW Link. 1302
BibRef

Tao, S.[Shuai], Kudo, M.[Mineichi], Nonaka, H.[Hidetoshi], Toyama, J.[Jun],
Camera view usage of binary infrared sensors for activity recognition,
ICPR12(1759-1762).
WWW Link. 1302
BibRef

Li, K.[Kang], Fu, Y.[Yun],
ARMA-HMM: A new approach for early recognition of human activity,
ICPR12(1779-1782).
WWW Link. 1302
BibRef

Tu, P.[Peter], Gao, D.[Dashan], Yu, T.[Ting], Yao, Y.[Yi],
Action based video summarization for convenience stores,
ICIP12(45-48).
IEEE DOI 1302
BibRef

Cullen, D.[Daniel], Konrad, J.[Janusz], Little, T.D.C.,
Detection and Summarization of Salient Events in Coastal Environments,
AVSS12(7-12).
IEEE DOI 1211
BibRef

Walker, J.[Jacob], Gupta, A.[Abhinav], Hebert, M.[Martial],
Patch to the Future: Unsupervised Visual Prediction,
CVPR14(3302-3309)
IEEE DOI 1409
Activity Forecasting; Prediction mid-level visual elements and temporal modeling. BibRef

Odobez, J.M.[Jean-Marc], Carincotte, C.[Cyril], Emonet, R.[Rémi], Jouneau, E.[Erwan], Zaidenberg, S.[Sofia], Ravera, B.[Bertrand], Bremond, F.[Francois], Grifoni, A.[Andrea],
Unsupervised Activity Analysis and Monitoring Algorithms for Effective Surveillance Systems,
ECCVDemos12(III: 675-678).
Springer DOI 1210
BibRef

Stottinger, J.[Julian], Uijlings, J.R.R.[Jasper R. R.], Pandey, A.K.[Anand K.], Sebe, N.[Nicu], Giunchiglia, F.[Fausto],
(Unseen) event recognition via semantic compositionality,
CVPR12(3061-3068).
IEEE DOI 1208
High level events built from image level events BibRef

Rahman, T., Xu, B., Sigal, L.,
Watch, Listen and Tell: Multi-Modal Weakly Supervised Dense Event Captioning,
ICCV19(8907-8916)
IEEE DOI 2004
audio signal processing, audio-visual systems, feature extraction, gesture recognition, image classification, Mel frequency cepstral coefficient BibRef

Bajaj, M., Wang, L., Sigal, L.,
G3raphGround: Graph-Based Language Grounding,
ICCV19(4280-4289)
IEEE DOI 2004
graph theory, image capture, image representation, image segmentation, natural language processing, neural nets, Encoding BibRef