16.7.4.7.4 Human Activities, Interacting with Objects

Cavallaro, R.H.[Richard H.], Gepner, J.N.[Jerry N.], Gloudemans, J.R.[James R.], Honey, S.K.[Stanley K.], Squadron, W.F.[William F.], White, M.S.[Marvin S.],
System for determining the position of an object,
US_Patent6,133,946, Oct 17, 2000
WWW Link. BibRef 0010

Cavallaro, R.H.[Richard H.], Gloudemans, J.R.[James R.], Honey, S.K.[Stanley K.], O'Brien, T.J.[Terence J.], Phillips, A.C.[Alan C.], Squadron, W.F.[William F.], White, M.S.[Marvin S.],
System for determining the end of a path for a moving object,
US_Patent6,304,665, Oct 16, 2001
WWW Link. BibRef 0110

Gupta, A.[Abhinav], Kembhavi, A.[Aniruddha], Davis, L.S.[Larry S.],
Observing Human-Object Interactions: Using Spatial and Functional Compatibility for Recognition,
PAMI(31), No. 10, October 2009, pp. 1775-1789.
IEEE DOI 0909
Understand events, recognize motions, recognize the objects. Apply constraints to reduce computation. BibRef

Jiang, Y.G.[Yu-Gang], Li, Z., Chang, S.F.[Shih-Fu],
Modeling Scene and Object Contexts for Human Action Retrieval With Few Examples,
CirSysVideo(21), No. 5, May 2011, pp. 674-681.
IEEE DOI 1105
Context from the background scene. Based on 10 basic actions. BibRef

Liu, Y.[Yuan], Ma, L.[Lin], Zhang, Y.F.[Yi-Feng], Liu, W.[Wei], Chang, S.F.[Shih-Fu],
Multi-Granularity Generator for Temporal Action Proposal,
CVPR19(3599-3608).
IEEE DOI 2002
BibRef

Shou, Z.[Zheng], Gao, H.[Hang], Zhang, L.[Lei], Miyazawa, K.[Kazuyuki], Chang, S.F.[Shih-Fu],
AutoLoc: Weakly-Supervised Temporal Action Localization in Untrimmed Videos,
ECCV18(XVI: 162-179).
Springer DOI 1810
BibRef

Shou, Z.[Zheng], Wang, D.A.[Dong-Ang], Chang, S.F.[Shih-Fu],
Temporal Action Localization in Untrimmed Videos via Multi-stage CNNs,
CVPR16(1049-1058)
IEEE DOI 1612
BibRef

Shou, Z.[Zheng], Chan, J., Zareian, A., Miyazawa, K., Chang, S.F.[Shih-Fu],
CDC: Convolutional-De-Convolutional Networks for Precise Temporal Action Localization in Untrimmed Videos,
CVPR17(1417-1426)
IEEE DOI 1711
Convolution, Feature extraction, Kernel, Proposals, Semantics, Videos BibRef

Filipovych, R.[Roman], Ribeiro, E.[Eraldo],
Robust sequence alignment for actor-object interaction recognition: Discovering actor-object states,
CVIU(115), No. 2, February 2011, pp. 177-193.
Elsevier DOI 1102
BibRef
Earlier:
Recognizing primitive interactions by exploring actor-object states,
CVPR08(1-7).
IEEE DOI 0806
Activity analysis; Human-object interaction; Sequence matching; Dynamic programming BibRef

Filipovych, R.[Roman], Ribeiro, E.[Eraldo],
Learning Structural Models in Multiple Projection Spaces,
ICIAR09(616-626).
Springer DOI 0907
BibRef
Earlier:
Learning human motion models from unsegmented videos,
CVPR08(1-7).
IEEE DOI 0806
BibRef
Earlier:
Combining Models of Pose and Dynamics for Human Motion Recognition,
ISVC07(II: 21-32).
Springer DOI 0711
BibRef
And:
Learning Repetitive Patterns for Classifying Non-Rigidly Deforming Texture Surfaces,
CIAP07(49-54).
IEEE DOI 0709
BibRef
And:
Learning Basic Patterns from Repetitive Texture Surfaces Under Non-rigid Deformations,
ICIAR07(81-92).
Springer DOI 0708
BibRef

Filipovych, R.[Roman], Ribeiro, E.[Eraldo],
Adaptive Tuboid Shapes for Action Recognition,
ISVC09(II: 367-376).
Springer DOI 0911
BibRef

Filipovych, R.[Roman], Ribeiro, E.[Eraldo],
Determining the scale of interest regions in videos,
ICIP09(985-988).
IEEE DOI 0911
BibRef

Yao, B.P.[Bang-Peng], Fei-Fei, L.[Li],
Recognizing Human-Object Interactions in Still Images by Modeling the Mutual Context of Objects and Human Poses,
PAMI(34), No. 9, September 2012, pp. 1691-1703.
IEEE DOI 1208
BibRef
Earlier:
Modeling mutual context of object and human pose in human-object Interaction activities,
CVPR10(17-24).
IEEE DOI Video of talk:
WWW Link. 1006
Award, CVPR, Student HM. BibRef

Yao, B.P.[Bang-Peng], Fei-Fei, L.[Li],
Grouplet: A structured image representation for recognizing human and object interactions,
CVPR10(9-16).
IEEE DOI Video of talk:
WWW Link. 1006
BibRef

Yao, B.P.[Bang-Peng], Fei-Fei, L.[Li],
Action Recognition with Exemplar Based 2.5D Graph Matching,
ECCV12(IV: 173-186).
Springer DOI 1210
BibRef

Yao, B.P.[Bang-Peng], Jiang, X.Y.[Xiao-Ye], Khosla, A.[Aditya], Lin, A.L.[Andy Lai], Guibas, L.J.[Leonidas J.], Fei-Fei, L.[Li],
Human action recognition by learning bases of action attributes and parts,
ICCV11(1331-1338).
IEEE DOI 1201
Attributes of pose and basic actions. BibRef

Zhu, Y.[Yuke], Fathi, A.[Alireza], Fei-Fei, L.[Li],
Reasoning about Object Affordances in a Knowledge Base Representation,
ECCV14(II: 408-424).
Springer DOI 1408
BibRef

Cheng, S.C.[Shyi-Chyi], Cheng, K.Y.[Kwang-Yu], Chen, Y.P.P.[Yi-Ping Phoebe],
GHT-based associative memory learning and its application to Human action detection and classification,
PR(46), No. 11, November 2013, pp. 3117-3128.
Elsevier DOI 1306
Action object shapes; Generalized Hough transform; Associative memory; Hypergraph; Human action detection and recognition BibRef

Liu, H.W.[Hao-Wei], Philipose, M.[Matthai], Pettersson, M.[Martin], Sun, M.T.[Ming-Ting],
Recognizing object manipulation activities using depth and visual cues,
JVCIR(25), No. 4, 2014, pp. 719-726.
Elsevier DOI 1403
Activity recognition
See also Automatic objects segmentation with RGB-D cameras. BibRef

Richtsfeld, A.[Andreas], Mörwald, T.[Thomas], Prankl, J.[Johann], Zillich, M.[Michael], Vincze, M.[Markus],
Learning of perceptual grouping for object segmentation on RGB-D data,
JVCIR(25), No. 1, 2014, pp. 64-73.
Elsevier DOI 1502
Computer vision BibRef

Fäulhammer, T., Zillich, M.[Michael], Prankl, J.[Johann], Vincze, M.[Markus],
A multi-modal RGB-D object recognizer,
ICPR16(733-738)
IEEE DOI 1705
Cameras, Computational modeling, Feature extraction, Pipelines, Shape, Training BibRef

Cavallo, A., Falco, P.,
Online Segmentation and Classification of Manipulation Actions From the Observation of Kinetostatic Data,
HMS(44), No. 2, April 2014, pp. 256-269.
IEEE DOI 1404
image classification BibRef

Xie, Z.G.[Zhi-Ge], Xiong, Y.S.[Yue-Shan], Xu, K.[Kai],
AB3D: action-based 3D descriptor for shape analysis,
VC(30), No. 6-8, June 2014, pp. 591-601.
Springer DOI 1407
BibRef
Earlier: Erratum: VC(30), No. 9, September 2014, pp. 1071.
WWW Link. 1410
3D models for human interactions. Graphics. BibRef

Darby, J.[John], Li, B.H.[Bai-Hua], Costen, N.P.[Nicholas P.],
Tracking object poses in the context of robust body pose estimates,
CVIU(127), No. 1, 2014, pp. 57-72.
Elsevier DOI 1408
Human-object interaction BibRef

Darby, J.[John], Li, B.H.[Bai-Hua], Cunningham, R.[Ryan], Costen, N.P.[Nicholas P.],
Object localisation via action recognition,
ICPR12(817-820).
WWW Link. 1302
Track objects in use by people BibRef

Hu, J.F.[Jian-Fang], Zheng, W.S.[Wei-Shi], Lai, J.H.[Jian-Huang], Gong, S.G.[Shao-Gang], Xiang, T.[Tao],
Exemplar-Based Recognition of Human: Object Interactions,
CirSysVideo(26), No. 4, April 2016, pp. 647-660.
IEEE DOI 1604
BibRef
Earlier:
Recognising Human-Object Interaction via Exemplar Based Modelling,
ICCV13(3144-3151)
IEEE DOI 1403
image matching. Human-Object Interaction; action recognition; exemplar modelling BibRef

Bazzica, A.[Alessio], Liem, C.C.S.[Cynthia C.S.], Hanjalic, A.[Alan],
On detecting the playing/non-playing activity of musicians in symphonic music videos,
CVIU(144), No. 1, 2016, pp. 188-204.
Elsevier DOI 1604
Cross-modal analysis BibRef

Malmir, M.[Mohsen], Sikka, K.[Karan], Forster, D.[Deborah], Fasel, I.[Ian], Movellan, J.R.[Javier R.], Cottrell, G.W.[Garrison W.],
Deep active object recognition by joint label and action prediction,
CVIU(156), No. 1, 2017, pp. 128-137.
Elsevier DOI 1702
BibRef
Earlier: A1, A2, A3, A5, A6, Only:
Deep Q-learning for Active Recognition of GERMS: Baseline performance on a standardized dataset for active learning,
BMVC15(xx-yy).
DOI Link 1601
Active object recognition in the context of human robot interaction. BibRef

Srikantha, A.[Abhilash], Gall, J.[Juergen],
Weak supervision for detecting object classes from activities,
CVIU(156), No. 1, 2017, pp. 138-150.
Elsevier DOI 1702
BibRef
Earlier:
Human Pose as Context for Object Detection,
BMVC15(xx-yy).
DOI Link 1601
Weakly supervised BibRef

Aksoy, E.E.[Eren Erdal], Orhan, A.[Adil], Wörgötter, F.[Florentin],
Semantic Decomposition and Recognition of Long and Complex Manipulation Action Sequences,
IJCV(122), No. 1, March 2017, pp. 84-115.
Springer DOI 1702
BibRef

Wei, P.[Ping], Zhao, Y.B.[Yi-Biao], Zheng, N.N.[Nan-Ning], Zhu, S.C.[Song-Chun],
Modeling 4D Human-Object Interactions for Joint Event Segmentation, Recognition, and Object Localization,
PAMI(39), No. 6, June 2017, pp. 1165-1179.
IEEE DOI 1705
BibRef
Earlier:
Modeling 4D Human-Object Interactions for Event and Object Recognition,
ICCV13(3272-3279)
IEEE DOI 1403
Context modeling, Hidden Markov models, Robots, Semantics, Video sequences, Human-object interaction, event recognition, object affordance, object localization, sequence, segmentation BibRef

Pajarinen, J.[Joni], Kyrki, V.[Ville],
Robotic manipulation of multiple objects as a POMDP,
AI(247), No. 1, 2017, pp. 213-228.
Elsevier DOI 1705
POMDP BibRef

Matsuo, T.[Tadashi], Shimada, N.[Nobutaka],
Construction of Latent Descriptor Space and Inference Model of Hand-Object Interactions,
IEICE(E100-D), No. 6, June 2017, pp. 1350-1359.
WWW Link. 1706
BibRef

Yu, H.N.[Hao-Nan], Siskind, J.M.[Jeffrey Mark],
Sentence Directed Video Object Codiscovery,
IJCV(124), No. 3, September 2017, pp. 312-334.
Springer DOI 1708
Not just large objects in the scene. BibRef

Meng, M.[Meng], Drira, H.[Hassen], Boonaert, J.[Jacques],
Distances evolution analysis for online and off-line human object interaction recognition,
IVC(70), 2018, pp. 32-45.
Elsevier DOI 1804
BibRef
And: Corrigendum: IVC(72), 2018, pp. 39.
Elsevier DOI 1804
Human object interaction, Rate invariance, Shape analysis, Temporal modeling BibRef

Truong, A.M.[Anh Minh], Yoshitaka, A.[Atsuo],
Structured RNN for human interaction,
IET-CV(12), No. 6, September 2018, pp. 817-825.
DOI Link 1808
BibRef
Earlier:
Structured LSTM for human-object interaction detection and anticipation,
AVSS17(1-6)
IEEE DOI 1806
image motion analysis, image sequences, learning (artificial intelligence), neural nets, Recurrent neural networks BibRef

Roy, A.[Abhinaba], Banerjee, B.[Biplab], Murino, V.[Vittorio],
Discriminative body part interaction mining for mid-level action representation and classification,
JVCIR(55), 2018, pp. 829-840.
Elsevier DOI 1809
Action recognition, Mid level feature, Zero shot learning BibRef

Ghodsi, S.[Saeed], Mohammadzade, H.[Hoda], Korki, E.[Erfan],
Simultaneous joint and object trajectory templates for human activity recognition from 3-D data,
JVCIR(55), 2018, pp. 729-741.
Elsevier DOI 1809
Human activity recognition, RGB-D sensors, Trajectory-based representation, Action template, Human object interaction BibRef

Ma, C.Y.[Chih-Yao], Chen, M.H.[Min-Hung], Kira, Z.[Zsolt], Al Regib, G.[Ghassan],
TS-LSTM and temporal-inception: Exploiting spatiotemporal dynamics for activity recognition,
SP:IC(71), 2019, pp. 76-87.
Elsevier DOI 1901
Video understanding, Action recognition, Convolutional neural network, Recurrent neural network BibRef

Chen, M.H.[Min-Hung], Li, B.P.[Bao-Pu], Bao, Y.Z.[Ying-Ze], Al Regib, G.[Ghassan], Kira, Z.[Zsolt],
Action Segmentation With Joint Self-Supervised Temporal Domain Adaptation,
CVPR20(9451-9460)
IEEE DOI 2008
Videos, Task analysis, Adaptation models, Convolution, Training, Predictive models, Training data BibRef

Chen, M., Li, B., Bao, Y., Al Regib, G.[Ghassan],
Action Segmentation with Mixed Temporal Domain Adaptation,
WACV20(594-603)
IEEE DOI 2006
Videos, Adaptation models, Feature extraction, Generators, Neural networks, Decoding, Video surveillance BibRef

Ma, C.Y.[Chih-Yao], Kadav, A., Melvin, I., Kira, Z.[Zsolt], Al Regib, G.[Ghassan], Graf, H.P.,
Attend and Interact: Higher-Order Object Interactions for Video Understanding,
CVPR18(6790-6800)
IEEE DOI 1812
Visualization, Task analysis, Computational modeling, Image color analysis, Marine vehicles, Cognition, Feature extraction BibRef

Chen, C.P.[Cheng-Peng], Min, W.Q.[Wei-Qing], Li, X.[Xue], Jiang, S.Q.[Shu-Qiang],
Hybrid incremental learning of new data and new classes for hand-held object recognition,
JVCIR(58), 2019, pp. 138-148.
Elsevier DOI 1901
Incremental learning, Object recognition, SVM, Human-machine interaction BibRef

Ehrhardt, S.[Sebastien], Monszpart, A.[Aron], Mitra, N.J.[Niloy J.], Vedaldi, A.[Andrea],
Taking visual motion prediction to new heightfields,
CVIU(181), 2019, pp. 14-25.
Elsevier DOI 1903
Modeling physical interactions between objects. BibRef

Kim, S., Yun, K., Park, J., Choi, J.Y.,
Skeleton-Based Action Recognition of People Handling Objects,
WACV19(61-70)
IEEE DOI 1904
feature extraction, graph theory, image representation, object detection, object recognition, pose estimation, Detectors BibRef

Bayraktar, E.[Ertugrul], Yigit, C.B.[Cihat Bora], Boyraz, P.[Pinar],
A hybrid image dataset toward bridging the gap between real and simulation environments for robotics,
MVA(30), No. 1, February 2019, pp. 23-40.
Springer DOI 1904
BibRef

Zhang, H.[Hao], Ngo, C.W.[Chong-Wah],
A Fine Granularity Object-Level Representation for Event Detection and Recounting,
MultMed(21), No. 6, June 2019, pp. 1450-1463.
IEEE DOI 1906
Events involve interactions between people and objects. Feature extraction, Event detection, Encoding, Visualization, Training, Streaming media, Semantics, search result reasoning BibRef

Li, X.D.[Xu-Dong], Ye, M.[Mao], Liu, Y.G.[Yi-Guang], Zhu, C.[Ce],
Adaptive Deep Convolutional Neural Networks for Scene-Specific Object Detection,
CirSysVideo(29), No. 9, September 2019, pp. 2538-2551.
IEEE DOI 1909
Object detection, Feature extraction, Surveillance, Kernel, Adaptation models, Detectors, Linear programming, surveillance scene BibRef

Xu, B., Li, J., Wong, Y., Zhao, Q., Kankanhalli, M.S.,
Interact as You Intend: Intention-Driven Human-Object Interaction Detection,
MultMed(22), No. 6, June 2020, pp. 1423-1432.
IEEE DOI 2005
Visualization, Task analysis, Object detection, Image recognition, Feature extraction, Computational modeling, Semantics, Visual Relationships BibRef

Sandino, J.[Juan], Vanegas, F.[Fernando], Maire, F.[Frederic], Caccetta, P.[Peter], Sanderson, C.[Conrad], Gonzalez, F.[Felipe],
UAV Framework for Autonomous Onboard Navigation and People/Object Detection in Cluttered Indoor Environments,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Wolf, O.O.[Oliver Olsen], Wiggins, G.A.[Geraint A.],
Look! It's Moving! Is It Alive? How Movement Affects Humans' Affinity Living and Non-Living Entities,
AffCom(11), No. 4, October 2020, pp. 669-683.
IEEE DOI 2011
Human perception of movement. Robots, Anthropomorphism, Animals, Linguistics, Animation, Observers, Measurement, Animacy, expressiveness, language, metaphors, quantitative methods BibRef

Zhang, H.B.[Han-Bo], Lan, X.G.[Xu-Guang], Zhou, X.W.[Xin-Wen], Tian, Z.Q.[Zhi-Qiang], Zhang, Y.[Yang], Zheng, N.N.[Nan-Ning],
Visual manipulation relationship recognition in object-stacking scenes,
PRL(140), 2020, pp. 34-42.
Elsevier DOI 2012
Visual manipulation relationship, Grasp precondition, Robot vision BibRef

Lin, T.W.[Tian-Wei], Zhao, X.[Xu], Su, H.S.[Hai-Sheng],
Joint Learning of Local and Global Context for Temporal Action Proposal Generation,
CirSysVideo(30), No. 12, December 2020, pp. 4899-4912.
IEEE DOI 2012
Proposals, Videos, Task analysis, Reliability, Convolution, Object detection, Robots, Temporal action proposal generation, untrimmed video BibRef

Qing, Z.W.[Zhi-Wu], Su, H.S.[Hai-Sheng], Gan, W.H.[Wei-Hao], Wang, D.L.[Dong-Liang], Wu, W.[Wei], Wang, X.[Xiang], Qiao, Y.[Yu], Yan, J.J.[Jun-Jie], Gao, C.X.[Chang-Xin], Sang, N.[Nong],
Temporal Context Aggregation Network for Temporal Action Proposal Refinement,
CVPR21(485-494)
IEEE DOI 2111
Location awareness, Benchmark testing, Reliability engineering, Pattern recognition, Proposals, Task analysis BibRef

Fan, Z.X.[Zhao-Xuan], Zhao, X.[Xu], Lin, T.W.[Tian-Wei], Su, H.S.[Hai-Sheng],
Attention-Based Multiview Re-Observation Fusion Network for Skeletal Action Recognition,
MultMed(21), No. 2, February 2019, pp. 363-374.
IEEE DOI 1902
Skeleton, Nonhomogeneous media, Fuses, Task analysis, Visualization, Pose estimation, long short-term memory (LSTM) BibRef

Su, H.S.[Hai-Sheng], Zhao, X.[Xu], Lin, T.W.[Tian-Wei],
Cascaded Pyramid Mining Network for Weakly Supervised Temporal Action Localization,
ACCV18(II:558-574).
Springer DOI 1906
BibRef

Liu, S.M.[Shu-Ming], Zhao, X.[Xu], Su, H.S.[Hai-Sheng], Hu, Z.L.[Zhi-Lan],
TSI: Temporal Scale Invariant Network for Action Proposal Generation,
ACCV20(V:530-546).
Springer DOI 2103
BibRef

Lin, T.W.[Tian-Wei], Zhao, X.[Xu], Su, H.S.[Hai-Sheng], Wang, C.J.[Chong-Jing], Yang, M.[Ming],
BSN: Boundary Sensitive Network for Temporal Action Proposal Generation,
ECCV18(II: 3-21).
Springer DOI 1810
BibRef

Ji, Z.[Zhong], Liu, X.Y.[Xi-Yao], Pang, Y.W.[Yan-Wei], Ouyang, W.L.[Wang-Li], Li, X.L.[Xue-Long],
Few-Shot Human-Object Interaction Recognition With Semantic-Guided Attentive Prototypes Network,
IP(30), 2021, pp. 1648-1661.
IEEE DOI 2101
Prototypes, Task analysis, Training, Computational modeling, Visualization, Semantics, Explosions, Few-shot learning, graph convolutional network BibRef

Zhong, X.B.[Xu-Bin], Ding, C.X.[Chang-Xing], Qu, X.[Xian], Tao, D.C.[Da-Cheng],
Polysemy Deciphering Network for Robust Human-Object Interaction Detection,
IJCV(129), No. 6, June 2021, pp. 1910-1929.
Springer DOI 2106
BibRef
Earlier:
Polysemy Deciphering Network for Human-object Interaction Detection,
ECCV20(XX:69-85).
Springer DOI 2011
BibRef

Subramanian, R.R.[R. Raja], Vasudevan, V.,
A deep genetic algorithm for human activity recognition leveraging fog computing frameworks,
JVCIR(77), 2021, pp. 103132.
Elsevier DOI 2106
Deep genetic algorithm, Human activity recognition, Fog computing, Ambulatory healthcare BibRef

Amer, A.Y.A.[Ahmed Youssef Ali], Aerts, J.M.[Jean-Marie], Vanrumste, B.[Bart], Luca, S.[Stijn],
A Localized Learning Approach Applied to Human Activity Recognition,
IEEE_Int_Sys(36), No. 3, May 2021, pp. 58-71.
IEEE DOI 2107
Support vector machines, Feature extraction, Hidden Markov models, Training, Data models, Mathematical model, least-squares support vector machine BibRef

Wang, H.R.[Hao-Ran], Jiao, L.C.[Li-Cheng], Liu, F.[Fang], Li, L.L.[Ling-Ling], Liu, X.[Xu], Ji, D.[Deyi], Gan, W.H.[Wei-Hao],
IPGN: Interactiveness Proposal Graph Network for Human-Object Interaction Detection,
IP(30), 2021, pp. 6583-6593.
IEEE DOI 2108
Task analysis, Proposals, Visualization, Semantics, Pose estimation, Message passing, Knowledge engineering, interaction learning BibRef

Li, Y.L.[Yong-Lu], Liu, X.P.[Xin-Peng], Wu, X.Q.[Xiao-Qian], Huang, X.J.[Xi-Jie], Xu, L.[Liang], Lu, C.[Cewu],
Transferable Interactiveness Knowledge for Human-Object Interaction Detection,
PAMI(44), No. 7, July 2022, pp. 3870-3882.
IEEE DOI 2206
Feature extraction, Visualization, Image edge detection, Biological system modeling, Task analysis, Semantics, transfer learning BibRef

Li, Y.L.[Yong-Lu], Zhou, S.Y.[Si-Yuan], Huang, X.J.[Xi-Jie], Xu, L.[Liang], Ma, Z.[Ze], Fang, H.S.[Hao-Shu], Wang, Y.F.[Yan-Feng], Lu, C.[Cewu],
Transferable Interactiveness Knowledge for Human-Object Interaction Detection,
CVPR19(3580-3589).
IEEE DOI 2002
BibRef

Kogashi, K.[Kaen], Wu, Y.[Yang], Nobuhara, S.[Shohei], Nishino, K.[Ko],
Human-Object Interaction Detection with Missing Objects,
IVC(113), 2021, pp. 104262.
Elsevier DOI 2108
BibRef
Earlier: MVA21(1-5)
DOI Link 2109
Human-object interaction BibRef

Gao, Y.M.[Yi-Ming], Kuang, Z.H.[Zhang-Hui], Li, G.B.[Guan-Bin], Zhang, W.[Wayne], Lin, L.[Liang],
Hierarchical Reasoning Network for Human-Object Interaction Detection,
IP(30), 2021, pp. 8306-8317.
IEEE DOI 2110
Visualization, Cognition, Correlation, Benchmark testing, Task analysis, Sports, Periodic structures, graph neural network BibRef

Kim, D.J.[Dong-Jin], Sun, X.[Xiao], Choi, J.[Jinsoo], Lin, S.[Stephen], Kweon, I.S.[In So],
ACP++: Action Co-Occurrence Priors for Human-Object Interaction Detection,
IP(30), 2021, pp. 9150-9163.
IEEE DOI 2112
BibRef
Earlier:
Detecting Human-object Interactions with Action Co-occurrence Priors,
ECCV20(XXI:718-736).
Springer DOI 2011
Visualization, Training, Task analysis, Bicycles, Semantics, Context modeling, Benchmark testing, Human-object interaction, knowledge distillation BibRef

Yang, D.M.[Dong-Ming], Zou, Y.X.[Yue-Xian], Li, Z.[Zhu], Li, G.[Ge],
Learning Human-Object Interaction via Interactive Semantic Reasoning,
IP(30), 2021, pp. 9294-9305.
IEEE DOI 2112
Semantics, Visualization, Cognition, Feature extraction, Biological system modeling, Message passing, Neural networks, human body-part BibRef

Fan, H.[Hehe], Zhuo, T.[Tao], Yu, X.[Xin], Yang, Y.[Yi], Kankanhalli, M.[Mohan],
Understanding Atomic Hand-Object Interaction With Human Intention,
CirSysVideo(32), No. 1, January 2022, pp. 275-285.
IEEE DOI 2201
Videos, Cognition, Pattern recognition, Fans, Task analysis, Neural networks, deep neural networks BibRef

Wang, T.[Ting], Ng, W.W.Y.[Wing W. Y.], Li, J.[Jinde], Wu, Q.X.[Qiu-Xia], Zhang, S.[Shuai], Nugent, C.[Chris], Shewell, C.[Colin],
A Deep Clustering via Automatic Feature Embedded Learning for Human Activity Recognition,
CirSysVideo(32), No. 1, January 2022, pp. 210-223.
IEEE DOI 2201
Feature extraction, Clustering algorithms, Clustering methods, Visualization, Activity recognition, Vocabulary, Task analysis, autoencoder BibRef

Shakerian, R.[Reza], Yadollahzadeh-Tabari, M.[Meisam], Rad, S.Y.B.[Seyed Yaser Bozorgi],
Proposing a Fuzzy Soft-max-based classifier in a hybrid deep learning architecture for human activity recognition,
IET-Bio(11), No. 2, 2022, pp. 171-186.
DOI Link 2202
deep learning, Fuzzy, Human Activity Recognition (HAR), soft-max classifier BibRef

Li, Z.M.[Zong-Mian], Sedlar, J.[Jiri], Carpentier, J.[Justin], Laptev, I.[Ivan], Mansard, N.[Nicolas], Sivic, J.[Josef],
Estimating 3D Motion and Forces of Human-Object Interactions from Internet Videos,
IJCV(130), No. 2, February 2022, pp. 363-383.
Springer DOI 2202
BibRef
Earlier:
Estimating 3D Motion and Forces of Person-Object Interactions From Monocular Video,
CVPR19(8632-8641).
IEEE DOI 2002
BibRef

Liu, L.[Lu], Tan, R.T.[Robby T.],
Human object interaction detection using two-direction spatial enhancement and exclusive object prior,
PR(124), 2022, pp. 108438.
Elsevier DOI 2203
Human-object interaction detection, Two-direction spatial enhancement, Exclusive object prior, Non-interactive suppression BibRef

Jin, Y.[Yang], Jiang, W.H.[Wen-Hao], Yang, Y.[Yi], Mu, Y.D.[Ya-Dong],
Zero-Shot Video Event Detection With High-Order Semantic Concept Discovery and Matching,
MultMed(24), No. 2022, pp. 1896-1908.
IEEE DOI 2204
Semantics, Event detection, Visualization, Libraries, Streaming media, Task analysis, Feature extraction, high-order concept BibRef

Ghadi, Y.Y.[Yazeed Yasin], Waheed, M.[Manahil], al Shloul, T.[Tamara], Alsuhibany, S.A.[Suliman A.], Jalal, A.[Ahmad], Park, J.[Jeongmin],
Automated Parts-Based Model for Recognizing Human-Object Interactions from Aerial Imagery with Fully Convolutional Network,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Zhou, T.F.[Tian-Fei], Qi, S.Y.[Si-Yuan], Wang, W.G.[Wen-Guan], Shen, J.B.[Jian-Bing], Zhu, S.C.[Song-Chun],
Cascaded Parsing of Human-Object Interaction Recognition,
PAMI(44), No. 6, June 2022, pp. 2827-2840.
IEEE DOI 2205
Portable computers, Neural networks, Cognition, Task analysis, Image segmentation, Context modeling, Visualization, fine-grained relation segmentation BibRef

Zhou, T.F.[Tian-Fei], Wang, W.G.[Wen-Guan], Qi, S.Y.[Si-Yuan], Ling, H., Shen, J.B.[Jian-Bing],
Cascaded Human-Object Interaction Recognition,
CVPR20(4262-4271)
IEEE DOI 2008
Semantics, Task analysis, Pipelines, Proposals, Visualization, Computer vision BibRef

Xu, K.L.[Kun-Lun], Li, Z.M.[Zhi-Min], Zhang, Z.J.[Zhi-Jun], Dong, L.Z.[Lei-Zhen], Xu, W.H.[Wen-Hui], Yan, L.X.[Lu-Xin], Zhong, S.[Sheng], Zou, X.[Xu],
Effective actor-centric human-object interaction detection,
IVC(121), 2022, pp. 104422.
Elsevier DOI 2205
Human-object interaction detection, Global context utilizing, Pixel-wise prediction, Deep learning BibRef

Yang, D.M.[Dong-Ming], Zou, Y.X.[Yue-Xian], Zhang, C.[Can], Cao, M.[Meng], Chen, J.[Jie],
RR-Net: Relation Reasoning for End-to-End Human-Object Interaction Detection,
CirSysVideo(32), No. 6, June 2022, pp. 3853-3865.
IEEE DOI 2206
Cognition, Detectors, Visualization, Feature extraction, Semantics, Proposals, Encoding, Relation reasoning, end-to-end BibRef

Khaire, P.[Pushpajit], Kumar, P.[Praveen],
Deep learning and RGB-D based human action, human-human and human-object interaction recognition: A survey,
JVCIR(86), 2022, pp. 103531.
Elsevier DOI 2206
Human action recognition, CNN, LSTM, Human-human interaction, Human-object interaction, Deep learning, RGB-D sensors, GCN BibRef

Nie, L.S.[Lan-Shun], Li, X.[Xue], Gong, T.Y.[Tian-Ying], Zhan, D.[Dechen],
Few shot learning-based fast adaptation for human activity recognition,
PRL(159), 2022, pp. 100-107.
Elsevier DOI 2206
BibRef

Buoncompagni, L.[Luca], Kareem, S.Y.[Syed Yusha], Mastrogiovanni, F.[Fulvio],
Human Activity Recognition Models in Ontology Networks,
Cyber(52), No. 6, June 2022, pp. 5587-5606.
IEEE DOI 2207
Ontologies, Activity recognition, Knowledge engineering, Smart homes, Hidden Markov models, semantic networks BibRef

Liu, S.[Si], Wang, Z.[Zitian], Gao, Y.[Yulu], Ren, L.[Lejian], Liao, Y.[Yue], Ren, G.H.[Guang-Hui], Li, B.[Bo], Yan, S.C.[Shui-Cheng],
Human-Centric Relation Segmentation: Dataset and Solution,
PAMI(44), No. 9, September 2022, pp. 4987-5001.
IEEE DOI 2208
Person In Context (PIC) dataset for this new task, which contains 17,122 high-resolution images. Task analysis, Image segmentation, Visualization, Semantics, Robots, Kernel, Silicon, Human-centric relation segmentation, matching, visual relation detection BibRef

Yu, J.H.[Jia-Hui], Gao, H.W.[Hong-Wei], Chen, Y.Q.[Yong-Quan], Zhou, D.[Dalin], Liu, J.G.[Jin-Guo], Ju, Z.J.[Zhao-Jie],
Deep Object Detector With Attentional Spatiotemporal LSTM for Space Human-Robot Interaction,
HMS(52), No. 4, August 2022, pp. 784-793.
IEEE DOI 2208
Feature extraction, Videos, Detectors, Robots, Semantics, Object detection, Real-time systems, Attention model, video object detection BibRef

Shrivastava, R.[Rahul], Tiwari, V.[Vivek], Jain, S.[Swati], Tiwari, B.[Basant], Kushwaha, A.K.S.[Alok Kumar Singh], Singh, V.P.[Vibhav Prakash],
A role-entity based human activity recognition using inter-body features and temporal sequence memory,
IET-IPR(16), No. 11, 2022, pp. 2911-2921.
DOI Link 2208
BibRef

Liu, X.L.[Xiao-Long], Bai, S.[Song], Bai, X.[Xiang],
An Empirical Study of End-to-End Temporal Action Detection,
CVPR22(19978-19987)
IEEE DOI 2210
Training, Codes, Computational modeling, Semantics, Buildings, Detectors, Action and event recognition, Video analysis and understanding BibRef

Liu, X.L.[Xiao-Long], Wang, Q.M.[Qi-Meng], Hu, Y.[Yao], Tang, X.[Xu], Zhang, S.W.[Shi-Wei], Bai, S.[Song], Bai, X.[Xiang],
End-to-End Temporal Action Detection With Transformer,
IP(31), 2022, pp. 5427-5441.
IEEE DOI 2208
Pipelines, Transformers, Proposals, Training, Feature extraction, Task analysis, Detectors, Transformer, temporal action detection, action recognition BibRef

Zeng, F.G.[Fan-Gao], Dong, B.[Bin], Zhang, Y.[Yuang], Wang, T.C.[Tian-Cai], Zhang, X.Y.[Xiang-Yu], Wei, Y.C.[Yi-Chen],
MOTR: End-to-End Multiple-Object Tracking with Transformer,
ECCV22(XXVII:659-675).
Springer DOI 2211
BibRef

Zou, C.[Cheng], Wang, B.H.[Bo-Han], Hu, Y.[Yue], Liu, J.Q.[Jun-Qi], Wu, Q.[Qian], Zhao, Y.[Yu], Li, B.[Boxun], Zhang, C.G.[Chen-Guang], Zhang, C.[Chi], Wei, Y.C.[Yi-Chen], Sun, J.[Jian],
End-to-End Human Object Interaction Detection with HOI Transformer,
CVPR21(11820-11829)
IEEE DOI 2111
Pipelines, Force, Object detection, Transformer cores, Streaming media, Transformers BibRef

Wang, J.F.[Jian-Feng], Song, L.[Lin], Li, Z.M.[Ze-Ming], Sun, H.B.[Hong-Bin], Sun, J.[Jian], Zheng, N.N.[Nan-Ning],
End-to-End Object Detection with Fully Convolutional Network,
CVPR21(15844-15853)
IEEE DOI 2111
Convolutional codes, Training, Filtering, Detectors, Object detection BibRef

Xu, M.D.[Meng-De], Zhang, Z.[Zheng], Hu, H.[Han], Wang, J.F.[Jian-Feng], Wang, L.J.[Li-Juan], Wei, F.Y.[Fang-Yun], Bai, X.[Xiang], Liu, Z.C.[Zi-Cheng],
End-to-End Semi-Supervised Object Detection with Soft Teacher,
ICCV21(3040-3049)
IEEE DOI 2203
Training, Image segmentation, Computational modeling, Object detection, Detectors, Benchmark testing, Transfer/Low-shot/Semi/Unsupervised Learning BibRef

Wang, T.C.[Tian-Cai], Yang, T.[Tong], Danelljan, M.[Martin], Khan, F.S.[Fahad Shahbaz], Zhang, X.Y.[Xiang-Yu], Sun, J.[Jian],
Learning Human-Object Interaction Detection Using Interaction Points,
CVPR20(4115-4124)
IEEE DOI 2008
Object detection, Feature extraction, Detectors, Heating systems, Streaming media, Visualization BibRef

Wang, T.C.[Tian-Cai], Anwer, R.M.[Rao Muhammad], Khan, M.H.[Muhammad Haris], Khan, F.S.[Fahad Shahbaz], Pang, Y.W.[Yan-Wei], Shao, L.[Ling], Laaksonen, J.T.[Jorma T.],
Deep Contextual Attention for Human-Object Interaction Detection,
ICCV19(5693-5701)
IEEE DOI 2004
feature extraction, image representation, learning (artificial intelligence), object detection, Visualization BibRef

Li, Q.Y.[Qi-Yue], Xie, X.M.[Xue-Mei], Zhang, J.[Jin], Shi, G.M.[Guang-Ming],
Language-guided graph parsing attention network for human-object interaction recognition,
JVCIR(89), 2022, pp. 103640.
Elsevier DOI 2212
Human-object interaction, Language-guided, Graph parsing attention network, Word embedding BibRef

Bai, L.[Lin], Chen, F.[Fenglian], Tian, Y.[Yang],
Automatically detecting human-object interaction by an instance part-level attention deep framework,
PR(134), 2023, pp. 109110.
Elsevier DOI 2212
Human-object interaction, Instance part-level correlations, Self-attention-based model, Image context BibRef

Lim, J.Y.[Jun-Yi], Baskaran, V.M.[Vishnu Monn], Lim, J.M.Y.[Joanne Mun-Yee], Wong, K.S.[Kok-Sheik], See, J.[John], Tistarelli, M.[Massimo],
ERNet: An Efficient and Reliable Human-Object Interaction Detection Network,
IP(32), 2023, pp. 964-979.
IEEE DOI 2301
Training, Adaptation models, Uncertainty, Estimation, Feature extraction, Transformers, Decoding, uncertainty estimation BibRef

Antoun, M.[Maya], Asmar, D.[Daniel],
Human object interaction detection: Design and survey,
IVC(130), 2023, pp. 104617.
Elsevier DOI 2301
Human object interaction, Scene understanding, Deep learning BibRef

Xu, Z.J.[Zhi-Jing], Huang, J.J.[Jia-Jing], Huang, K.[Kan],
A novel computer vision-based approach for monitoring safety harness use in construction,
IET-IPR(17), No. 4, 2023, pp. 1071-1085.
DOI Link 2303
computer vision, construction industry, object detection BibRef

Cheng, Y.M.[Ya-Min], Wang, Z.[Zhi], Zhan, W.H.[Wen-Han], Duan, H.C.[Han-Cong],
Multi-Scale Human-Object Interaction Detector,
CirSysVideo(33), No. 4, April 2023, pp. 1827-1838.
IEEE DOI 2304
Transformers, Detectors, Computer architecture, Task analysis, Decoding, Iterative decoding, Feature extraction, multi-scale BibRef

Sudhakaran, S.[Swathikiran], Escalera, S.[Sergio], Lanz, O.[Oswald],
Learning to Recognize Actions on Objects in Egocentric Video With Attention Dictionaries,
PAMI(45), No. 6, June 2023, pp. 6674-6687.
IEEE DOI 2305
Feature extraction, Cameras, Visualization, Task analysis, Optical imaging, Logic gates, Encoding, Egocentric vision, video classification BibRef

Zeng, Z.T.[Zhi-Tao], Dai, P.W.[Peng-Wen], Zhang, X.[Xuan], Zhang, L.[Lei], Cao, X.C.[Xiao-Chun],
Cognition Guided Human-Object Relationship Detection,
IP(32), 2023, pp. 2468-2480.
IEEE DOI 2305
Feature extraction, Videos, Head, Solid modeling, Brain modeling, Visualization, Human-object relationship, head pose, body pose, eye-head-body movements BibRef

Ye, Q.[Qing], Wang, X.[Xikun], Li, R.[Rui], Zhang, Y.[Yongmei],
Human object interaction detection based on feature optimization and key human-object enhancement,
JVCIR(93), 2023, pp. 103824.
Elsevier DOI 2305
Human object interaction detection, FOFR-CNN, Key human-object enhancement, Graph convolutional network BibRef

Ni, Z.F.[Zhi-Fan], Valls-Mascaró, E.[Esteve], Ahn, H.[Hyemin], Lee, D.[Dongheui],
Human-object interaction prediction in videos through gaze following,
CVIU(233), 2023, pp. 103741.
Elsevier DOI 2307
Human-object interaction prediction, Semantic scene understanding, Spatial-temporal transformer BibRef

Aboukhadra, A.T.[Ahmed Tawfik], Malik, J.[Jameel], Elhayek, A.[Ahmed], Robertini, N.[Nadia], Stricker, D.[Didier],
THOR-Net: End-to-end Graformer-based Realistic Two Hands and Object Reconstruction with Self-supervision,
WACV23(1001-1010)
IEEE DOI 2302
2 hands interacting. Water, Heating systems, Shape, Network topology, Pose estimation, Feature extraction, Algorithms: Biometrics, face, gesture, body pose BibRef

Agarwal, A.[Apoorva], Dabral, R.[Rishabh], Jain, A.[Arjun], Ramakrishnan, G.[Ganesh],
Skew-Robust Human-Object Interactions in Videos,
WACV23(5087-5096)
IEEE DOI 2302
Visualization, Protocols, Pipelines, Image representation, Solids, Videos, visual reasoning BibRef

Yu, Z.C.[Ze-Cheng], Huang, Y.F.[Yi-Fei], Furuta, R.[Ryosuke], Yagi, T.[Takuma], Goutsu, Y.[Yusuke], Sato, Y.[Yoichi],
Fine-grained Affordance Annotation for Egocentric Hand-Object Interaction Videos,
WACV23(2154-2162)
IEEE DOI 2302
Annotations, Affordances, Manuals, Predictive models, Task analysis, Videos BibRef

Wang, R.[Rong], Mao, W.[Wei], Li, H.D.[Hong-Dong],
Interacting Hand-Object Pose Estimation via Dense Mutual Attention,
WACV23(5724-5734)
IEEE DOI 2302
Correlation, Codes, Computational modeling, Pose estimation, Benchmark testing, Real-time systems, Algorithms: Biometrics, face, Virtual/augmented reality BibRef

Huang, Z.T.[Zi-Ting], Zhen, Q.[Qing], Guo, C.[Cong], Shi, X.F.[Xiang-Feng], Zhang, Y.J.[Yu-Jie], Zhao, X.B.[Xin-Bo],
Object Detection of Tobacco-Related Information Based on Visual Features,
ICIVC22(135-144)
IEEE DOI 2301
Are people smoking? Visualization, Image recognition, Text recognition, Target recognition, Software algorithms, Object detection, tobacco-related case BibRef

Gutzeit, L.[Lisa],
Hierarchical Segmentation of Human Manipulation Movements,
ICPR22(2742-2748)
IEEE DOI 2212
Training, Tracking, Motion segmentation, Training data, Inference algorithms, Classification algorithms BibRef

Guermal, M.[Mohammed], Dai, R.[Rui], Brémond, F.[François],
THORN: Temporal Human-Object Relation Network for Action Recognition,
ICPR22(3303-3309)
IEEE DOI 2212
Visualization, Solid modeling, Computational modeling, Object detection, Predictive models, Robustness BibRef

Yang, B.X.[Bai-Xiang], Gao, W.[Wei], Li, G.[Ge],
Focus and Adjust: Progressive Refinement Network for Human Object Interaction Detection,
ICPR22(2546-2552)
IEEE DOI 2212
Location awareness, Visualization, Semantics, Detectors, Predictive models, Benchmark testing, Transformers BibRef

Almushyti, M.[Muna], Li, F.W.B.[Frederick W. B.],
STIT: Spatio-Temporal Interaction Transformers for Human-Object Interaction Recognition in Videos,
ICPR22(3287-3294)
IEEE DOI 2212
Deep learning, Transformers, Videos, Context modeling BibRef

Wang, G.Z.[Guang-Zhi], Guo, Y.Y.[Yang-Yang], Wong, Y.K.[Yong-Kang], Kankanhalli, M.[Mohan],
Chairs Can Be Stood On: Overcoming Object Bias in Human-Object Interaction Detection,
ECCV22(XXIV:654-672).
Springer DOI 2211
BibRef

Xie, X.H.[Xiang-Hui], Bhatnagar, B.L.[Bharat Lal], Pons-Moll, G.[Gerard],
CHORE: Contact, Human and Object Reconstruction from a Single RGB Image,
ECCV22(II:125-145).
Springer DOI 2211
BibRef

Zhao, K.F.[Kai-Feng], Wang, S.F.[Shao-Fei], Zhang, Y.[Yan], Beeler, T.[Thabo], Tang, S.[Siyu],
Compositional Human-Scene Interaction Synthesis with Semantic Control,
ECCV22(VI:311-327).
Springer DOI 2211
BibRef

Zhou, K.[Keyang], Bhatnagar, B.L.[Bharat Lal], Lenssen, J.E.[Jan Eric], Pons-Moll, G.[Gerard],
TOCH: Spatio-Temporal Object-to-Hand Correspondence for Motion Refinement,
ECCV22(III:1-19).
Springer DOI 2211
BibRef

Walsman, A.[Aaron], Zhang, M.[Muru], Kotar, K.[Klemen], Desingh, K.[Karthik], Farhadi, A.[Ali], Fox, D.[Dieter],
Break and Make: Interactive Structural Understanding Using LEGO Bricks,
ECCV22(XXVIII:90-107).
Springer DOI 2211
BibRef

Guo, Q.P.[Qing-Pei], Yao, K.S.[Kai-Sheng], Chu, W.[Wei],
Switch-BERT: Learning to Model Multimodal Interactions by Switching Attention and Input,
ECCV22(XXXVI:330-346).
Springer DOI 2211
BibRef

Wang, Y.F.[Yi-Fan], Wu, R.[Ruihai], Mo, K.[Kaichun], Ke, J.Q.[Jia-Qi], Fan, Q.[Qingnan], Guibas, L.J.[Leonidas J.], Dong, H.[Hao],
AdaAfford: Learning to Adapt Manipulation Affordance for 3D Articulated Objects via Few-Shot Interactions,
ECCV22(XXIX:90-107).
Springer DOI 2211
BibRef

Wang, Y.[Yuan], Sun, R.[Rui], Zhang, Z.[Zhe], Zhang, T.Z.[Tian-Zhu],
Adaptive Agent Transformer for Few-Shot Segmentation,
ECCV22(XXIX:36-52).
Springer DOI 2211
BibRef

Wu, X.Q.[Xiao-Qian], Li, Y.L.[Yong-Lu], Liu, X.P.[Xin-Peng], Zhang, J.[Junyi], Wu, Y.Z.[Yu-Zhe], Lu, C.[Cewu],
Mining Cross-Person Cues for Body-Part Interactiveness Learning in HOI Detection,
ECCV22(IV:121-136).
Springer DOI 2211
Human-Object Interaction. BibRef

Zhong, X.[Xubin], Ding, C.X.[Chang-Xing], Li, Z.J.[Zi-Jian], Huang, S.L.[Shao-Li],
Towards Hard-Positive Query Mining for DETR-Based Human-Object Interaction Detection,
ECCV22(XXVII:444-460).
Springer DOI 2211
BibRef

Zhang, X.H.[Xiao-Han], Bhatnagar, B.L.[Bharat Lal], Starke, S.[Sebastian], Guzov, V.[Vladimir], Pons-Moll, G.[Gerard],
COUCH: Towards Controllable Human-Chair Interactions,
ECCV22(V:518-535).
Springer DOI 2211
BibRef

Tu, D.Y.[Dan-Yang], Min, X.K.[Xiong-Kuo], Duan, H.Y.[Hui-Yu], Guo, G.D.[Guo-Dong], Zhai, G.T.[Guang-Tao], Shen, W.[Wei],
Iwin: Human-Object Interaction Detection via Transformer with Irregular Windows,
ECCV22(IV:87-103).
Springer DOI 2211
BibRef

Qiao, T.[Tanqiu], Men, Q.H.[Qian-Hui], Li, F.W.B.[Frederick W. B.], Kubotani, Y.[Yoshiki], Morishima, S.[Shigeo], Shum, H.P.H.[Hubert P. H.],
Geometric Features Informed Multi-person Human-Object Interaction Recognition in Videos,
ECCV22(IV:474-491).
Springer DOI 2211
BibRef

Soucek, T.[Tomáš], Alayrac, J.B.[Jean-Baptiste], Miech, A.[Antoine], Laptev, I.[Ivan], Sivic, J.[Josef],
Look for the Change: Learning Object States and State-Modifying Actions from Untrimmed Web Videos,
CVPR22(13936-13946)
IEEE DOI 2210
Training, Adaptation models, Training data, Footwear, Information filters, Pattern recognition, Internet, Self- semi- meta- unsupervised learning BibRef

Huang, C.H.P.[Chun-Hao P.], Yi, H.W.[Hong-Wei], Höschle, M.[Markus], Safroshkin, M.[Matvey], Alexiadis, T.[Tsvetelina], Polikovsky, S.[Senya], Scharstein, D.[Daniel], Black, M.J.[Michael J.],
Capturing and Inferring Dense Full-Body Human-Scene Contact,
CVPR22(13264-13275)
IEEE DOI 2210
Image resolution, Codes, Shape, Video sequences, Pose estimation, Transformers, Pose estimation and tracking, Datasets and evaluation BibRef

Iftekhar, A.S.M., Chen, H.[Hao], Kundu, K.[Kaustav], Li, X.Y.[Xin-Yu], Tighe, J.[Joseph], Modolo, D.[Davide],
What to look at and where: Semantic and Spatial Refined Transformer for detecting human-object interactions,
CVPR22(5343-5353)
IEEE DOI 2210
Image analysis, Semantics, Benchmark testing, Transformers, Feature extraction, Pattern recognition, Recognition: detection, Scene analysis and understanding BibRef

Jiang, Z.Y.[Zhen-Yu], Hsu, C.C.[Cheng-Chun], Zhu, Y.[Yuke],
Ditto: Building Digital Twins of Articulated Objects from Interaction,
CVPR22(5606-5616)
IEEE DOI 2210
Geometry, Visualization, Solid modeling, Buildings, Estimation, Virtual environments, 3D from multi-view and sensors, Representation learning BibRef

Jiang, Y.H.[Yu-Heng], Jiang, S.[Suyi], Sun, G.X.[Guo-Xing], Su, Z.[Zhuo], Guo, K.[Kaiwen], Wu, M.[Minye], Yu, J.Y.[Jing-Yi], Xu, L.[Lan],
NeuralHOFusion: Neural Volumetric Rendering under Human-object Interactions,
CVPR22(6145-6155)
IEEE DOI 2210
Geometry, Telepresence, Face recognition, Pose estimation, Pipelines, 3D from multi-view and sensors, Face and gestures, RGBD sensors and analytics BibRef

Bhatnagar, B.L.[Bharat Lal], Xie, X.H.[Xiang-Hui], Petrov, I.A.[Ilya A.], Sminchisescu, C.[Cristian], Theobalt, C.[Christian], Pons-Moll, G.[Gerard],
BEHAVE: Dataset and Method for Tracking Human Object Interactions,
CVPR22(15914-15925)
IEEE DOI 2210
Solid modeling, Codes, Pose estimation, Neural networks, Mixed reality, Predictive models, 3D from multi-view and sensors, Vision+graphics BibRef

Jiang, H.Z.[Huai-Zu], Ma, X.J.[Xiao-Jian], Nie, W.[Weili], Yu, Z.D.[Zhi-Ding], Zhu, Y.[Yuke], Anandkumar, A.[Anima],
Bongard-HOI: Benchmarking Few-Shot Visual Reasoning for Human-Object Interactions,
CVPR22(19034-19043)
IEEE DOI 2210
Training, Representation learning, Learning systems, Visualization, Image recognition, Benchmark testing, Predictive models, retrieval BibRef

Dong, L.Z.[Lei-Zhen], Li, Z.M.[Zhi-Min], Xu, K.L.[Kun-Lun], Zhang, Z.J.[Zhi-Jun], Yan, L.X.[Lu-Xin], Zhong, S.[Sheng], Zou, X.[Xu],
Category-Aware Transformer Network for Better Human-Object Interaction Detection,
CVPR22(19516-19525)
IEEE DOI 2210
Head, Image recognition, Semantics, Object detection, Detectors, Performance gain, Scene analysis and understanding, retrieval BibRef

Saha, A.[Avishkar], Mendez, O.[Oscar], Russell, C.[Chris], Bowden, R.[Richard],
'The Pedestrian next to the Lamppost' Adaptive Object Graphs for Better Instantaneous Mapping,
CVPR22(19506-19515)
IEEE DOI 2210
Location awareness, Image segmentation, Navigation, Convolution, Image edge detection, Message passing, 3D from single images BibRef

Zhang, Y.[Yong], Pan, Y.W.[Ying-Wei], Yao, T.[Ting], Huang, R.[Rui], Mei, T.[Tao], Chen, C.W.[Chang-Wen],
Exploring Structure-aware Transformer over Interaction Proposals for Human-Object Interaction Detection,
CVPR22(19526-19535)
IEEE DOI 2210
Image analysis, Codes, Semantics, Detectors, Benchmark testing, Transformers, Scene analysis and understanding BibRef

Qu, X.[Xian], Ding, C.X.[Chang-Xing], Li, X.[Xingao], Zhong, X.[Xubin], Tao, D.C.[Da-Cheng],
Distillation Using Oracle Queries for Transformer-based Human-Object Interaction Detection,
CVPR22(19536-19545)
IEEE DOI 2210
Training, Representation learning, Knowledge engineering, Image analysis, Codes, Computational modeling, Scene analysis and understanding BibRef

Zhou, D.[Desen], Liu, Z.C.[Zhi-Chao], Wang, J.[Jian], Wang, L.[Leshan], Hu, T.[Tao], Ding, E.[Errui], Wang, J.D.[Jing-Dong],
Human-Object Interaction Detection via Disentangled Transformer,
CVPR22(19546-19555)
IEEE DOI 2210
Location awareness, Visualization, Codes, Benchmark testing, Transformers, Decoding, Scene analysis and understanding, grouping and shape analysis BibRef

Zhang, F.Z.[Frederic Z.], Campbell, D.[Dylan], Gould, S.[Stephen],
Efficient Two-Stage Detection of Human-Object Interactions with a Novel Unary-Pairwise Transformer,
CVPR22(20072-20080)
IEEE DOI 2210
Visualization, Memory management, Graphics processing units, Detectors, Transformers, Real-time systems, Pattern recognition, retrieval BibRef

Liu, X.P.[Xin-Peng], Li, Y.L.[Yong-Lu], Wu, X.Q.[Xiao-Qian], Tai, Y.W.[Yu-Wing], Lu, C.[Cewu], Tang, C.K.[Chi-Keung],
Interactiveness Field in Human-Object Interactions,
CVPR22(20081-20090)
IEEE DOI 2210
Codes, Benchmark testing, Pattern recognition, Action and event recognition, Recognition: detection, Scene analysis and understanding BibRef

Liu, Y.Z.[Yun-Ze], Liu, Y.[Yun], Jiang, C.[Che], Lyu, K.[Kangbo], Wan, W.[Weikang], Shen, H.[Hao], Liang, B.Q.[Bo-Qiang], Fu, Z.[Zhoujie], Wang, H.[He], Yi, L.[Li],
HOI4D: A 4D Egocentric Dataset for Category-Level Human-Object Interaction,
CVPR22(20981-20990)
IEEE DOI 2210
Point cloud compression, Visualization, Target tracking, Annotations, Shape, Datasets and evaluation, grouping and shape analysis BibRef

Liao, Y.[Yue], Zhang, A.[Aixi], Lu, M.[Miao], Wang, Y.L.[Yong-Liang], Li, X.B.[Xiao-Bo], Liu, S.[Si],
GEN-VLKT: Simplify Association and Enhance Interaction Understanding for HOI Detection,
CVPR22(20091-20100)
IEEE DOI 2210
Training, Visualization, Pipelines, Detectors, Feature extraction, Decoding, Action and event recognition, Behavior analysis, Vision+language BibRef

Ou, Y.J.[Yang-Jun], Mi, L.[Li], Chen, Z.Z.[Zhen-Zhong],
Object-Relation Reasoning Graph for Action Recognition,
CVPR22(20101-20110)
IEEE DOI 2210
Couplings, Visualization, Message passing, Semantics, Cognition, Pattern recognition, Action and event recognition, Visual reasoning BibRef

Yang, L.X.[Li-Xin], Li, K.[Kailin], Zhan, X.Y.[Xin-Yu], Wu, F.[Fei], Xu, A.[Anran], Liu, L.[Liu], Lu, C.[Cewu],
OakInk: A Large-scale Knowledge Repository for Understanding Hand-Object Interaction,
CVPR22(20921-20930)
IEEE DOI 2210
Visualization, Affordances, Knowledge based systems, Pose estimation, Ink, Benchmark testing, Handover, Pose estimation and tracking BibRef

Hampali, S.[Shreyas], Sarkar, S.D.[Sayan Deb], Rad, M.[Mahdi], Lepetit, V.[Vincent],
Keypoint Transformer: Solving Joint Identification in Challenging Hands and Object Interactions for Accurate 3D Pose Estimation,
CVPR22(11080-11090)
IEEE DOI 2210
Heating systems, Pose estimation, Detectors, Transformers, Pattern recognition, Pose estimation and tracking, Deep learning architectures and techniques BibRef

Goyal, M.[Mohit], Modi, S.[Sahil], Goyal, R.[Rishabh], Gupta, S.[Saurabh],
Human Hands as Probes for Interactive Object Understanding,
CVPR22(3283-3293)
IEEE DOI 2210
Affordances, Pattern recognition, Probes, Unsupervised learning, Videos, Video analysis and understanding, Self- semi- meta- unsupervised learning BibRef

Ye, Y.F.[Yu-Fei], Gupta, A.[Abhinav], Tulsiani, S.[Shubham],
What's in your hands? 3D Reconstruction of Generic Objects in Hands,
CVPR22(3885-3895)
IEEE DOI 2210
Training, Visualization, Shape, Pose estimation, Rendering (computer graphics), Robustness, 3D from single images BibRef

Bhango, Z.[Zibusiso], van der Haar, D.[Dustin],
A Comparison of Deep Learning Methods for Inebriation Recognition in Humans,
CIAP22(I:610-620).
Springer DOI 2205
BibRef

Leonardi, R.[Rosario], Ragusa, F.[Francesco], Furnari, A.[Antonino], Farinella, G.M.[Giovanni Maria],
Egocentric Human-Object Interaction Detection Exploiting Synthetic Data,
CIAP22(II:237-248).
Springer DOI 2205
BibRef

Ji, J.W.[Jing-Wei], Desai, R.[Rishi], Niebles, J.C.[Juan Carlos],
Detecting Human-Object Relationships in Videos,
ICCV21(8086-8096)
IEEE DOI 2203
Visualization, Genomics, Predictive models, Transformers, Feature extraction, Cognition, Video analysis and understanding, Scene analysis and understanding BibRef

He, T.[Tao], Gao, L.[Lianli], Song, J.[Jingkuan], Li, Y.F.[Yuan-Fang],
Exploiting Scene Graphs for Human-Object Interaction Detection,
ICCV21(15964-15973)
IEEE DOI 2203
Visualization, Message passing, Computational modeling, Semantics, Layout, Benchmark testing, Action and behavior recognition, Scene analysis and understanding BibRef

Dabral, R.[Rishabh], Shimada, S.[Soshi], Jain, A.[Arjun], Theobalt, C.[Christian], Golyanik, V.[Vladislav],
Gravity-Aware Monocular 3D Human-Object Reconstruction,
ICCV21(12345-12354)
IEEE DOI 2203
Meters, Measurement, Estimation, Kinematics, Bones, Linear programming, 3D from a single image and shape-from-x, Motion and tracking BibRef

Zhang, F.Z.[Frederic Z.], Campbell, D.[Dylan], Gould, S.[Stephen],
Spatially Conditioned Graphs for Detecting Human-Object Interactions,
ICCV21(13299-13307)
IEEE DOI 2203
Computational modeling, Detectors, Feature extraction, Graph neural networks, Action and behavior recognition, Recognition and classification BibRef

Li, S.[Shuang], Du, Y.L.[Yi-Lun], Torralba, A.B.[Antonio B.], Sivic, J.[Josef], Russell, B.[Bryan],
Weakly Supervised Human-Object Interaction Detection in Video via Contrastive Spatiotemporal Regions,
ICCV21(1825-1835)
IEEE DOI 2203
Training, Vocabulary, Visualization, Annotations, Surveillance, Supervised learning, Search problems, Vision+language, Video analysis and understanding BibRef

Cao, Z.[Zhe], Radosavovic, I.[Ilija], Kanazawa, A.[Angjoo], Malik, J.[Jitendra],
Reconstructing Hand-Object Interactions in the Wild,
ICCV21(12397-12406)
IEEE DOI 2203
Solid modeling, Image reconstruction, 3D from a single image and shape-from-x, BibRef

Yang, L.X.[Li-Xin], Zhan, X.Y.[Xin-Yu], Li, K.[Kailin], Xu, W.Q.[Wen-Qiang], Li, J.F.[Jie-Feng], Lu, C.[Cewu],
CPF: Learning a Contact Potential Field to Model the Hand-Object Interaction,
ICCV21(11077-11086)
IEEE DOI 2203
Measurement, Deep learning, Codes, Pose estimation, Benchmark testing, Gestures and body pose, 3D from a single image and shape-from-x BibRef

Xu, B.[Bo], Huang, H.[Han], Lu, C.[Cheng], Li, Z.W.[Zi-Wen], Guo, Y.D.[Yan-Dong],
Virtual Multi-Modality Self-Supervised Foreground Matting for Human-Object Interaction,
ICCV21(428-437)
IEEE DOI 2203
Training, Heating systems, Image segmentation, Computer network reliability, Computational modeling, Vision applications and systems BibRef

Kwon, T.[Taein], Tekin, B.[Bugra], Stühmer, J.[Jan], Bogo, F.[Federica], Pollefeys, M.[Marc],
H2O: Two Hands Manipulating Objects for First Person Interaction Recognition,
ICCV21(10118-10128)
IEEE DOI 2203
Water, Point cloud compression, Solid modeling, Annotations, Pose estimation, Predictive models, Datasets and evaluation, Gestures and body pose BibRef

Moro, M.[Matteo], Casadio, M.[Maura], Mrotek, L.A.[Leigh Ann], Ranganathan, R.[Rajiv], Scheidt, R.[Robert], Odone, F.[Francesca],
On the Precision of Markerless 3d Semantic Features: An Experimental Study on Violin Playing,
ICIP21(2733-2737)
IEEE DOI 2201
Motor drives, Tracking, Filtering, Feature detection, Pipelines, Semantics, Marker-less, 3D Reconstruction, Human Motion Analysis, Semantic Features Detection BibRef

Nanyang, J.D.[Jiafei Duan], Jian, S.Y.B.[Samson Yu Bai], Tan, C.[Cheston],
SPACE: A Simulator for Physical Interactions and Causal Learning in 3D Environments,
SEAR21(2058-2063)
IEEE DOI 2112
Deep learning, Solid modeling, Stability analysis BibRef

Yang, W.H.[Wen-Hao], Song, Y.[Yinan], Zhao, Z.C.[Zhi-Cheng], Su, F.[Fei],
Instance Search via Fusing Hierarchical Multi-level Retrieval and Human-object Interaction Detection,
ViRaL21(2323-2327)
IEEE DOI 2112
Face recognition, Feature extraction BibRef

Chen, M.F.[Ming-Fei], Liao, Y.[Yue], Liu, S.[Si], Chen, Z.Y.[Zhi-Yuan], Wang, F.[Fei], Qian, C.[Chen],
Reformulating HOI Detection as Adaptive Set Prediction,
CVPR21(9000-9009)
IEEE DOI 2111
Human-Object Interaction. Training, Codes, Aggregates, Detectors, Feature extraction, Transformers BibRef

Min, C.H.[Cheol-Hui], Bae, J.[Jinseok], Lee, J.[Junho], Kim, Y.M.[Young Min],
GATSBI: Generative Agent-centric Spatio-temporal Object Interaction,
CVPR21(3073-3082)
IEEE DOI 2111
Visualization, Computational modeling, Transforms, Reinforcement learning, Predictive models, Trajectory, Spatiotemporal phenomena BibRef

Deng, S.H.[Sheng-Heng], Xu, X.[Xun], Wu, C.Z.[Chao-Zheng], Chen, K.[Ke], Jia, K.[Kui],
3D AffordanceNet: A Benchmark for Visual Object Affordance Understanding,
CVPR21(1778-1787)
IEEE DOI 2111
Ingeract with limited location. Deep learning, Visualization, Shape, Affordances, Semantics, Estimation BibRef

Chao, Y.W.[Yu-Wei], Yang, W.[Wei], Xiang, Y.[Yu], Molchanov, P.[Pavlo], Handa, A.[Ankur], Tremblay, J.[Jonathan], Narang, Y.S.[Yashraj S.], van Wyk, K.[Karl], Iqbal, U.[Umar], Birchfield, S.[Stan], Kautz, J.[Jan], Fox, D.[Dieter],
DexYCB: A Benchmark for Capturing Hand Grasping of Objects,
CVPR21(9040-9049)
IEEE DOI 2111
Pose estimation, Grasping, Benchmark testing, Handover, Drives BibRef

Ehsani, K.[Kiana], Han, W.[Winson], Herrasti, A.[Alvaro], VanderBilt, E.[Eli], Weihs, L.[Luca], Kolve, E.[Eric], Kembhavi, A.[Aniruddha], Mottaghi, R.[Roozbeh],
ManipulaTHOR: A Framework for Visual Object Manipulation,
CVPR21(4495-4504)
IEEE DOI 2111
Visualization, Navigation, Mobile agents, Grasping, Manipulators, Planning BibRef

Morais, R.[Romero], Le, V.[Vuong], Venkatesh, S.[Svetha], Tran, T.[Truyen],
Learning Asynchronous and Sparse Human-Object Interaction in Videos,
CVPR21(16036-16045)
IEEE DOI 2111
Analytical models, Adaptation models, Computational modeling, Affordances, Time series analysis, Pattern recognition BibRef

Hou, Z.[Zhi], Yu, B.S.[Bao-Sheng], Tao, D.C.[Da-Cheng],
Discovering Human-Object Interaction Concepts via Self-Compositional Learning,
ECCV22(XXVII:461-478).
Springer DOI 2211
BibRef

Hou, Z.[Zhi], Yu, B.S.[Bao-Sheng], Qiao, Y.[Yu], Peng, X.J.[Xiao-Jiang], Tao, D.C.[Da-Cheng],
Detecting Human-Object Interaction via Fabricated Compositional Learning,
CVPR21(14641-14650)
IEEE DOI 2111
Codes, Benchmark testing, Pattern recognition, Task analysis BibRef

Zhong, X.[Xubin], Qu, X.[Xian], Ding, C.X.[Chang-Xing], Tao, D.C.[Da-Cheng],
Glance and Gaze: Inferring Action-aware Points for One-Stage Human-Object Interaction Detection,
CVPR21(13229-13238)
IEEE DOI 2111
Adaptation models, Visualization, Codes, Color, Predictive models, Feature extraction BibRef

Bodla, N.[Navaneeth], Shrivastava, G.[Gaurav], Chellappa, R.[Rama], Shrivastava, A.[Abhinav],
Hierarchical Video Prediction using Relational Layouts for Human-Object Interactions,
CVPR21(12141-12150)
IEEE DOI 2111
Measurement, Recurrent neural networks, Computational modeling, Layout, Predictive models, Cognition BibRef

Tamura, M.[Masato], Ohashi, H.[Hiroki], Yoshinaga, T.[Tomoaki],
QPIC: Query-Based Pairwise Human-Object Interaction Detection with Image-Wide Contextual Information,
CVPR21(10405-10414)
IEEE DOI 2111
Graphical models, Codes, Aggregates, Detectors, Feature extraction, Transformers BibRef

Kim, B.[Bumsoo], Mun, J.[Jonghwan], On, K.W.[Kyoung-Woon], Shin, M.[Minchul], Lee, J.[Junhyun], Kim, E.S.[Eun-Sol],
MSTR: Multi-Scale Transformer for End-to-End Human-Object Interaction Detection,
CVPR22(19556-19565)
IEEE DOI 2210
Training, Image resolution, Semantics, Detectors, Benchmark testing, Transformers, Scene analysis and understanding BibRef

Kim, B.[Bumsoo], Lee, J.[Junhyun], Kang, J.[Jaewoo], Kim, E.S.[Eun-Sol], Kim, H.W.J.[Hyun-Woo J.],
HOTR: End-to-End Human-Object Interaction Detection with Transformers,
CVPR21(74-83)
IEEE DOI 2111
Training, Semantics, Detectors, Benchmark testing, Predictive models, Transformers, Prediction algorithms BibRef

Park, J.[Jihwan], Lee, S.[SeungJun], Heo, H.[Hwan], Choi, H.K.[Hyeong Kyu], Kim, H.W.J.[Hyun-Woo J.],
Consistency Learning via Decoding Path Augmentation for Transformers in Human Object Interaction Detection,
CVPR22(1009-1018)
IEEE DOI 2210
Visualization, Codes, Computational modeling, Object detection, Transformers, retrieval, Recognition: detection BibRef

Haidu, A.[Andrei], Zhang, X.Y.[Xiao-Yue], Beetz, M.[Michael],
Knowledge-Enabled Generation of Semantically Annotated Image Sequences of Manipulation Activities from VR Demonstrations,
CVS21(130-143).
Springer DOI 2109
BibRef

Manousaki, V.[Victoria], Papoutsakis, K.[Konstantinos], Argyros, A.[Antonis],
Action Prediction During Human-Object Interaction Based on DTW and Early Fusion of Human and Object Representations,
CVS21(169-179).
Springer DOI 2109
BibRef

Dabral, R.[Rishabh], Sarkar, S.[Srijon], Reddy, S.P.[Sai Praneeth], Ramakrishnan, G.[Ganesh],
Exploration of Spatial and Temporal Modeling Alternatives for HOI,
WACV21(2280-2289)
IEEE DOI 2106
Human-Object Interaction. Visualization, Pipelines, Benchmark testing, Feature extraction BibRef

Kumaraswamy, S.K.[Suresh Kirthi], Shi, M.J.[Miao-Jing], Kijak, E.[Ewa],
Detecting Human-Object Interaction with Mixed Supervision,
WACV21(1227-1236)
IEEE DOI 2106
Training, Learning systems, Annotations, Pipelines, Robustness BibRef

Ragusa, F.[Francesco], Furnari, A.[Antonino], Livatino, S.[Salvatore], Farinella, G.M.[Giovanni Maria],
The MECCANO Dataset: Understanding Human-Object Interactions from Egocentric Videos in an Industrial-like Domain,
WACV21(1568-1577)
IEEE DOI
WWW Link. 2106
Dataset, Interactions. Taxonomy, Motorcycles, Object detection, Tools, Object recognition BibRef

Amrani, H.[Hamza], Micucci, D.[Daniela], Napoletano, P.[Paolo],
Personalized Models in Human Activity Recognition using Deep Learning,
ICPR21(9682-9688)
IEEE DOI 2105
Deep learning, Performance evaluation, Adaptation models, Neural networks, Transfer learning, Software algorithms, Activity recognition BibRef

Chen, G.Y.[Guan-Yu], Chen, C.[Chong], Zhao, Z.C.[Zhi-Cheng], Su, F.[Fei],
Human-Centric Parsing Network for Human-Object Interaction Detection,
ICPR21(5488-5494)
IEEE DOI 2105
Knowledge engineering, Image edge detection, Message passing, Semantics, Redundancy, Feature extraction, Pattern recognition BibRef

Agarwal, A.[Aditya], Sen, B.[Bipasha],
An Approach Towards Action Recognition Using Part Based Hierarchical Fusion,
ISVC20(I:306-318).
Springer DOI 2103
BibRef

Beleza, S.R.A.[Suzana R. A.], Fukui, K.[Kazuhiro],
Slow Feature Subspace for Action Recognition,
FBE20(702-716).
Springer DOI 2103

See also Applying slow feature analysis to image sequences yields a rich repertoire of complex cell properties. BibRef

Zhang, S., Zhang, Y., Ma, Q., Black, M.J., Tang, S.,
PLACE: Proximity Learning of Articulation and Contact in 3D Environments,
3DV20(642-651)
IEEE DOI 2102
Solid modeling, Biological system modeling, Encoding, Semantics, Affordances BibRef

Kim, B.[Bumsoo], Choi, T.[Taeho], Kang, J.[Jaewoo], Kim, H.W.J.[Hyun-Woo J.],
Uniondet: Union-level Detector Towards Real-time Human-object Interaction Detection,
ECCV20(XV:498-514).
Springer DOI 2011
BibRef

Hou, Z.[Zhi], Yu, B.[Baosheng], Qiao, Y.[Yu], Peng, X.J.[Xiao-Jiang], Tao, D.C.[Da-Cheng],
Affordance Transfer Learning for Human-Object Interaction Detection,
CVPR21(495-504)
IEEE DOI 2111
Codes, Affordances, Computational modeling, Transfer learning, Cognition, Pattern recognition BibRef

Hou, Z.[Zhi], Peng, X.J.[Xiao-Jiang], Qiao, Y.[Yu], Tao, D.C.[Da-Cheng],
Visual Compositional Learning for Human-object Interaction Detection,
ECCV20(XV:584-600).
Springer DOI 2011
BibRef

Wang, H.[Hai], Zheng, W.S.[Wei-Shi], Yingbiao, L.[Ling],
Contextual Heterogeneous Graph Network for Human-object Interaction Detection,
ECCV20(XVII:248-264).
Springer DOI 2011
BibRef

Basit, A., Munir, M.A., Ali, M., Werghi, N., Mahmood, A.,
Localizing Firearm Carriers By Identifying Human-Object Pairs,
ICIP20(2031-2035)
IEEE DOI 2011
Adaptation models, Proposals, Task analysis, Detectors, Pose estimation, Classification algorithms, Object detection, Gun violence BibRef

Hussain, S.M.[S. Muzamil], Liu, L.[Liu], Xu, W.Q.[Wen-Qiang], Lu, C.[Cewu],
FPHA-Afford: A Domain-Specific Benchmark Dataset for Occluded Object Affordance Estimation in Human-Object-Robot Interaction,
ICIP20(1416-1420)
IEEE DOI 2011
Estimation, Videos, Robots, Semantics, Task analysis, Machine learning, Feature extraction, Human-Object-Robot Interaction, FPHA-Afford BibRef

Liu, Y.[Yang], Chen, Q.C.[Qing-Chao], Zisserman, A.[Andrew],
Amplifying Key Cues for Human-object-interaction Detection,
ECCV20(XIV:248-265).
Springer DOI 2011
BibRef

Liu, M.[Miao], Tang, S.[Siyu], Li, Y.[Yin], Rehg, J.M.[James M.],
Forecasting Human-object Interaction: Joint Prediction of Motor Attention and Actions in First Person Video,
ECCV20(I:704-721).
Springer DOI 2011
BibRef

Choi, J.[Jinwoo], Sharma, G.[Gaurav], Schulter, S.[Samuel], Huang, J.B.[Jia-Bin],
Shuffle and Attend: Video Domain Adaptation,
ECCV20(XII: 678-695).
Springer DOI 2010
human action recognition. BibRef

Gao, C.[Chen], Xu, J.R.[Jia-Rui], Zou, Y.L.[Yu-Liang], Huang, J.B.[Jia-Bin],
DRG: Dual Relation Graph for Human-object Interaction Detection,
ECCV20(XII: 696-712).
Springer DOI 2010
BibRef

Zhang, J.Y.[Jason Y.], Pepose, S.[Sam], Joo, H.[Hanbyul], Ramanan, D.[Deva], Malik, J.[Jitendra], Kanazawa, A.[Angjoo],
Perceiving 3d Human-object Spatial Arrangements from a Single Image in the Wild,
ECCV20(XII: 34-51).
Springer DOI 2010
BibRef

Liu, C.C.[Chen-Chen], Jin, Y.[Yang], Xu, K.H.[Ke-Han], Gong, G.Q.[Guo-Qiang], Mu, Y.D.[Ya-Dong],
Beyond Short-Term Snippet: Video Relation Detection With Spatio-Temporal Global Context,
CVPR20(10837-10846)
IEEE DOI 2008
Interacting objects. Proposals, Visualization, Feature extraction, Object detection, Task analysis, Tracking, Image segmentation BibRef

Ulutan, O., Iftekhar, A.S.M., Manjunath, B.S.,
VSGNet: Spatial Attention Network for Detecting Human Object Interactions Using Graph Convolutions,
CVPR20(13614-13623)
IEEE DOI 2008
Feature extraction, Visualization, Task analysis, Proposals, Object detection, Image edge detection, Convolutional codes BibRef

Liao, Y., Liu, S., Wang, F., Chen, Y., Qian, C., Feng, J.,
PPDM: Parallel Point Detection and Matching for Real-Time Human-Object Interaction Detection,
CVPR20(479-487)
IEEE DOI 2008
Proposals, Heating systems, Feature extraction, Task analysis, Object detection, Real-time systems, Visualization BibRef

Li, Y., Liu, X., Lu, H., Wang, S., Liu, J., Li, J., Lu, C.,
Detailed 2D-3D Joint Representation for Human-Object Interaction,
CVPR20(10163-10172)
IEEE DOI 2008
Shape, Face, Benchmark testing, Robustness, Pose estimation BibRef

Li, Z., Huang, Y., Cai, M., Sato, Y.,
Manipulation-Skill Assessment from Videos with Spatial Attention Network,
EPIC19(4385-4395)
IEEE DOI 2004
behavioural sciences computing, learning (artificial intelligence), medical computing, Video Analysis BibRef

Zhou, P., Chi, M.,
Relation Parsing Neural Network for Human-Object Interaction Detection,
ICCV19(843-851)
IEEE DOI 2004
graph theory, learning (artificial intelligence), neural nets, object detection, human-object interaction detection, Visualization BibRef

Nagarajan, T., Feichtenhofer, C., Grauman, K.,
Grounded Human-Object Interaction Hotspots From Video,
ICCV19(8687-8696)
IEEE DOI 2004

WWW Link. image segmentation, learning (artificial intelligence), object detection, Facebook BibRef

Wan, B., Zhou, D., Liu, Y., Li, R., He, X.,
Pose-Aware Multi-Level Feature Network for Human Object Interaction Detection,
ICCV19(9468-9477)
IEEE DOI 2004
image representation, object detection, pose-aware multilevel feature network, Neural networks BibRef

Gupta, T., Schwing, A., Hoiem, D.,
No-Frills Human-Object Interaction Detection: Factorization, Layout Encodings, and Training Techniques,
ICCV19(9676-9684)
IEEE DOI 2004
learning (artificial intelligence), object detection, human-object interaction detection, layout encodings, Feature extraction BibRef

Chen, Y., Huang, S., Yuan, T., Zhu, Y., Qi, S., Zhu, S.,
Holistic++ Scene Understanding: Single-View 3D Holistic Scene Parsing and Human Pose Estimation With Human-Object Interaction and Physical Commonsense,
ICCV19(8647-8656)
IEEE DOI 2004
cameras, graph theory, image reconstruction, inference mechanisms, Markov processes, Monte Carlo methods, object detection, Two dimensional displays BibRef

Xu, B.J.[Bing-Jie], Wong, Y.K.[Yong-Kang], Li, J.N.[Jun-Nan], Zhao, Q.[Qi], Kankanhalli, M.S.[Mohan S.],
Learning to Detect Human-Object Interactions With Knowledge,
CVPR19(2019-2028).
IEEE DOI 2002
BibRef

Chao, Y., Vijayanarasimhan, S., Seybold, B., Ross, D.A., Deng, J., Sukthankar, R.,
Rethinking the Faster R-CNN Architecture for Temporal Action Localization,
CVPR18(1130-1139)
IEEE DOI 1812
Proposals, Object detection, Feature extraction, Image segmentation, Computer architecture BibRef

Kawanishi, Y., Murase, H., Xu, J., Tasaka, K., Yanagihara, H.,
Which Content in a Booklet is he/she Reading? Reading Content Estimation using an Indoor Surveillance Camera,
ICPR18(1731-1736)
IEEE DOI 1812
Estimation, Cameras, Feature extraction, Databases, Surveillance, Focusing, Face BibRef

Gkioxari, G., Girshick, R., Dollár, P., He, K.,
Detecting and Recognizing Human-Object Interactions,
CVPR18(8359-8367)
IEEE DOI 1812
Feature extraction, Visualization, Object detection, Predictive models, Task analysis, Target recognition, Image recognition BibRef

Kato, K.[Keizo], Li, Y.[Yin], Gupta, A.[Abhinav],
Compositional Learning for Human Object Interaction,
ECCV18(XIV: 247-264).
Springer DOI 1810
BibRef

Tsoli, A.[Aggeliki], Argyros, A.A.[Antonis A.],
Joint 3D Tracking of a Deformable Object in Interaction with a Hand,
ECCV18(XIV: 504-520).
Springer DOI 1810
BibRef

Tian, Y.P.[Ya-Peng], Shi, J.[Jing], Li, B.[Bochen], Duan, Z.Y.[Zhi-Yao], Xu, C.L.[Chen-Liang],
Audio-Visual Event Localization in Unconstrained Videos,
ECCV18(II: 252-268).
Springer DOI 1810
BibRef

Zhao, H.[Hang], Gan, C.[Chuang], Rouditchenko, A.[Andrew], Vondrick, C.[Carl], McDermott, J.[Josh], Torralba, A.B.[Antonio B.],
The Sound of Pixels,
ECCV18(I: 587-604).
Springer DOI 1810
BibRef

Gao, R.[Ruohan], Feris, R.[Rogerio], Grauman, K.[Kristen],
Learning to Separate Object Sounds by Watching Unlabeled Video,
ECCV18(III: 36-54).
Springer DOI 1810
Results:
WWW Link. Audio-visual interactions. BibRef

Pandey, R.[Rohit], Pidlypenskyi, P.[Pavel], Yang, S.[Shuoran], Kaeser-Chen, C.[Christine],
Efficient 6-DoF Tracking of Handheld Objects from an Egocentric Viewpoint,
ECCV18(II: 426-441).
Springer DOI 1810
BibRef

Fang, H.S.[Hao-Shu], Cao, J.[Jinkun], Tai, Y.W.[Yu-Wing], Lu, C.[Cewu],
Pairwise Body-Part Attention for Recognizing Human-Object Interactions,
ECCV18(X: 52-68).
Springer DOI 1810
BibRef

Qi, S.Y.[Si-Yuan], Wang, W.G.[Wen-Guan], Jia, B.X.[Bao-Xiong], Shen, J.B.[Jian-Bing], Zhu, S.C.[Song-Chun],
Learning Human-Object Interactions by Graph Parsing Neural Networks,
ECCV18(IX: 407-423).
Springer DOI 1810
BibRef

Huang, T., McKenna, S.J.[Stephen J.],
Sequential Recognition of Manipulation Actions Using Discriminative Superpixel Group Mining,
ICIP18(579-583)
IEEE DOI 1809
Color, Histograms, Training, Image segmentation, Oils, Detectors, Superpixel grouping, Human-object interaction, Action recognition BibRef

Shen, L.Y.[Li-Yue], Yeung, S.[Serena], Hoffman, J.[Judy], Mori, G.[Greg], Fei-Fei, L.[Li],
Scaling Human-Object Interaction Recognition Through Zero-Shot Learning,
WACV18(1568-1576)
IEEE DOI 1806
learning (artificial intelligence), object recognition, HICODET dataset, HOI recognition, fully-supervised HOI detection, Visualization BibRef

Chao, Y.W., Liu, Y., Liu, X., Zeng, H., Deng, J.,
Learning to Detect Human-Object Interactions,
WACV18(381-389)
IEEE DOI 1806
image classification, neural nets, object detection, object recognition, DNN input, HICO-DET, HO-RCNN, Semantics BibRef

Pirk, S., Diamanti, O., Thibert, B., Xu, D., Guibas, L.,
Shape-aware spatio-temporal descriptors for interaction classification,
ICIP17(4527-4531)
IEEE DOI 1803
Layout, Robot sensing systems, Sensor phenomena and characterization, Shape, scene analysis BibRef

Alayrac, J.B., Sivic, J.[Josef], Laptev, I.[Ivan], Lacoste-Julien, S.[Simon],
Joint Discovery of Object States and Manipulation Actions,
ICCV17(2146-2155)
IEEE DOI 1802
image motion analysis, image sequences, manipulators, pattern clustering, video signal processing, action recognition, Videos BibRef

Suchan, J., Bhatt, M.,
Commonsense Scene Semantics for Cognitive Robotics: Towards Grounding Embodied Visuo-Locomotive Interactions,
AutoRob17(742-750)
IEEE DOI 1802
Cognition, Computational modeling, Grounding, Robot sensing systems, Semantics, Space stations BibRef

Moltisanti, D.[Davide], Wray, M.[Michael], Mayol-Cuevas, W.W.[Walterio W.], Damen, D.[Dima],
Trespassing the Boundaries: Labeling Temporal Bounds for Object Interactions in Egocentric Video,
ICCV17(2905-2913)
IEEE DOI 1802
convolution, image annotation, neural nets, object detection, object recognition, video signal processing, Rubicon Boundaries, BibRef

Wang, X.L.[Xiao-Long], Girdhar, R.[Rohit], Gupta, A.[Abhinav],
Binge Watching: Scaling Affordance Learning from Sitcoms,
CVPR17(3366-3375)
IEEE DOI 1711
Dataset for learning work. Manuals, Robots, Semantics, TV, Videos BibRef

Schröder, M., Ritter, H.,
Hand-Object Interaction Detection with Fully Convolutional Networks,
ActionCh17(1236-1243)
IEEE DOI 1709
Convolutional codes, Data models, Decoding, Labeling, Object tracking, Real-time, systems BibRef

Sermanet, P.[Pierre], Lynch, C.[Corey], Hsu, J.[Jasmine], Levine, S.[Sergey],
Time-Contrastive Networks: Self-Supervised Learning from Multi-view Observation,
DeepLearnRV17(486-487)
IEEE DOI 1709
Loss measurement, Robots, Training, Videos BibRef

Fire, A.[Amy], Zhu, S.C.[Song-Chun],
Inferring Hidden Statuses and Actions in Video by Causal Reasoning,
Cognition17(48-56)
IEEE DOI 1709
Hidden features of actions. Cognition, Feature extraction, Grammar, Hidden Markov models, Monitoring, Switches BibRef

Junokas, M.J., Kohlburn, G., Lane, B., Kumar, S., Fu, W.T., Lindgren, R.,
Gestural Interactions of Embodied Educational Technology Using One-Shot Machine Learning,
FG17(996-996)
IEEE DOI 1707
Adaptation models, Educational technology, Feature extraction, Gesture recognition, Hidden Markov models, Magnetic cores, Training BibRef

Ji, Y.L.[Yan-Li], Li, J.[Jia_Ming], Cheng, H.[Hong], Xu, X.[Xing], Song, J.[Jingkuan],
Multi-cue Information Fusion for Two-Layer Activity Recognition,
HIS16(III: 273-285).
Springer DOI 1704
Body motion and object interaction (NN), fuse for activities. BibRef

Meng, M., Drira, H., Daoudi, M., Boonaert, J.,
Human Object Interaction Recognition Using Rate-Invariant Shape Analysis of Inter Joint Distances Trajectories,
DIFF-CV16(999-1004)
IEEE DOI 1612
BibRef

Kera, H., Yonetani, R., Higuchi, K., Sato, Y.,
Discovering Objects of Joint Attention via First-Person Sensing,
Egocentric-C16(361-369)
IEEE DOI 1612
BibRef

Zhu, Y.X.[Yi-Xin], Jiang, C.F.[Chen-Fanfu], Zhao, Y.B.[Yi-Biao], Terzopoulos, D.[Demetri], Zhu, S.C.[Song-Chun],
Inferring Forces and Learning Human Utilities from Videos,
CVPR16(3823-3833)
IEEE DOI 1612
physical quantities when body interacts with objects. BibRef

Pinto, L.[Lerrel], Gandhi, D.[Dhiraj], Han, Y.F.[Yuan-Feng], Park, Y.L.[Yong-Lae], Gupta, A.[Abhinav],
The Curious Robot: Learning Visual Representations via Physical Interactions,
ECCV16(II: 3-18).
Springer DOI 1611
BibRef

Mallya, A.[Arun], Lazebnik, S.[Svetlana],
Recurrent Models for Situation Recognition,
ICCV17(455-463)
IEEE DOI 1802
BibRef
Earlier:
Learning Models for Actions and Person-Object Interactions with Transfer to Question Answering,
ECCV16(I: 414-428).
Springer DOI 1611
random processes, recurrent neural nets, CRF-based models, Conditional Random Fields, RNN, BibRef

Hassan, M.[Mahmudul], Dharmaratne, A.[Anuja],
Attribute Based Affordance Detection from Human-Object Interaction Images,
RV15(220-232).
Springer DOI 1603
BibRef
And:
Labeling abnormalities in video based complex Human-Object Interactions by robust affordance modelling,
ICCVIA15(1-8)
IEEE DOI 1603
Bayes methods BibRef

Chao, Y.W., Wang, Z., He, Y., Wang, J., Deng, J.,
HICO: A Benchmark for Recognizing Human-Object Interactions in Images,
ICCV15(1017-1025)
IEEE DOI 1602
Benchmark testing BibRef

Sokeh, H.S.[Hajar Sadeghi], Gould, S.[Stephen], Renz, J.[Jochen],
Determining Interacting Objects in Human-Centric Activities via Qualitative Spatio-Temporal Reasoning,
ACCV14(V: 550-563).
Springer DOI 1504
BibRef

Chen, C.Y.[Chao-Yeh], Grauman, K.[Kristen],
Predicting the Location of 'interactees' in Novel Human-Object Interactions,
ACCV14(I: 351-367).
Springer DOI 1504
BibRef

Yu, G.[Gang], Liu, Z.C.[Zi-Cheng], Yuan, J.S.[Jun-Song],
Discriminative Orderlet Mining for Real-Time Recognition of Human-Object Interaction,
ACCV14(V: 50-65).
Springer DOI 1504
BibRef

Kluth, T.[Tobias], Nakath, D.[David], Reineking, T.[Thomas], Zetzsche, C.[Christoph], Schill, K.[Kerstin],
Affordance-Based Object Recognition Using Interactions Obtained from a Utility Maximization Principle,
Affordance14(406-412).
Springer DOI 1504
BibRef

Amiri, S.M.[S. Mohsen], Pourazad, M.T.[Mahsa T.], Nasiopoulos, P.[Panos], Leung, V.C.M.[Victor C.M.],
A similarity measure for analyzing human activities using human-object interaction context,
ICIP14(2368-2372)
IEEE DOI 1502
Accuracy BibRef

Parks, D.[Daniel], Itti, L.[Laurent],
Integrating human context and occlusion reasoning to improve handheld object tracking,
ICIP14(436-440)
IEEE DOI 1502
Cognition BibRef

Liu, J.[Jing], Wu, X.X.[Xin-Xiao], Feng, Y.[Yang],
Modeling the Relationship of Action, Object, and Scene,
ICPR14(2005-2010)
IEEE DOI 1412
Accuracy BibRef

Ubalde, S.[Sebastian], Liu, Z.C.[Zi-Cheng], Mejail, M.[Marta],
Detecting Subtle Human-Object Interactions Using Kinect,
CIARP14(770-777).
Springer DOI 1411
BibRef

Srikantha, A.[Abhilash], Gall, J.[Juergen],
Discovering Object Classes from Activities,
ECCV14(VI: 415-430).
Springer DOI 1408
BibRef

Arteta, C.[Carlos], Lempitsky, V.[Victor], Zisserman, A.[Andrew],
Counting in the Wild,
ECCV16(VII: 483-498).
Springer DOI 1611
BibRef

Arteta, C.[Carlos], Lempitsky, V.[Victor], Noble, J.A.[J. Alison], Zisserman, A.[Andrew],
Interactive Object Counting,
ECCV14(III: 504-518).
Springer DOI 1408
BibRef

Yang, G.[Guang], Yin, Y.F.[Ya-Feng], Man, H.[Hong],
Human object interactions recognition based on social network analysis,
AIPR13(1-4)
IEEE DOI 1408
computer vision BibRef

Rybok, L.[Lukas], Schauerte, B.[Boris], Al-Halah, Z.[Ziad], Stiefelhagen, R.[Rainer],
'Important stuff, everywhere!' Activity recognition with salient proto-objects as context,
WACV14(646-651)
IEEE DOI 1406
Accuracy BibRef

Escorcia, V., Niebles, J.C.[Juan Carlos],
Spatio-temporal Human-Object Interactions for Action Recognition in Videos,
HACI13(508-514)
IEEE DOI 1403
interactive systems BibRef

Yao, B.P.[Bang-Peng], Ma, J.Y.[Jia-Yuan], Fei-Fei, L.[Li],
Discovering Object Functionality,
ICCV13(2512-2519)
IEEE DOI 1403
from dataset of interactions. BibRef

Xie, D.[Dan], Todorovic, S.[Sinisa], Zhu, S.C.[Song-Chun],
Inferring 'Dark Matter' and 'Dark Energy' from Videos,
ICCV13(2224-2231)
IEEE DOI 1403
localizing functional objects in surveillance videos. Based on trajectories. BibRef

Ni, B.B.[Bing-Bing], Moulin, P.[Pierre],
Manipulation Pattern Discovery: A Nonparametric Bayesian Approach,
ICCV13(1361-1368)
IEEE DOI 1403
BibRef

Desai, C.[Chaitanya], Ramanan, D.[Deva],
Detecting Actions, Poses, and Objects with Relational Phraselets,
ECCV12(IV: 158-172).
Springer DOI 1210
BibRef

Packer, B.[Ben], Saenko, K.[Kate], Koller, D.[Daphne],
A combined pose, object, and feature model for action understanding,
CVPR12(1378-1385).
IEEE DOI 1208
BibRef

Zhang, B.[Bang], Ye, G.[Getian], Wang, Y.[Yang], Wang, W.[Wei], Xu, J.[Jie], Herman, G.[Gunawan], Yang, Y.[Yun],
Multi-class Graph Boosting with Subgraph Sharing for Object Recognition,
ICPR10(1541-1544).
IEEE DOI 1008
BibRef

Young, D.L.,
When to engage video resilience options,
AIPR13(1-8)
IEEE DOI 1408
error statistics BibRef

Young, D.L.,
Motion imagery metadata standards assist in object and activity classification,
AIPR10(1-4).
IEEE DOI 1010
BibRef

Utsumi, Y., Katte, M., Iwamura, M., Kise, K.,
Event Detection Based on Noisy Object Information,
ACPR13(572-575)
IEEE DOI 1408
object detection BibRef

Ren, S.G.[Shao-Gang], Sun, Y.[Yu],
Human-object-object-interaction affordance,
WORV13(1-6)
IEEE DOI 1307
Interaction with objects. BibRef

Kojima, A.[Atsuhiro], Miki, H.[Hiroshi], Kise, K.[Koichi],
Object Recognition Based on n-gram Expression of Human Actions,
ICPR10(372-375).
IEEE DOI 1008
BibRef

Tavakkoli, A.[Alireza], Nicolescu, M.[Mircea], Bebis, G.N.[George N.],
A Spatio-Spectral Algorithm for Robust and Scalable Object Tracking in Videos,
ISVC10(III: 161-170).
Springer DOI 1011
BibRef

Higuchi, M., Aoki, S., Kojima, A., Fukunaga, K.,
Scene recognition based on relationship between human actions and objects,
ICPR04(III: 73-78).
IEEE DOI 0409
BibRef

Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Actions, Grasping, Robot Grasping, Shape for Grasp .