@inproceedings{proposal,
  title={Proposal-free video grounding with contextual pyramid network},
  author={Li, Kun and Guo, Dan and Wang, Meng},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={35},
  number={3},
  pages={1902--1910},
  year={2021}
}

@inproceedings{iterative,
  title={Iterative context-aware graph inference for visual dialog},
  author={Guo, Dan and Wang, Hui and Zhang, Hanwang and Zha, Zheng-Jun and Wang, Meng},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={10055--10064},
  year={2020}
}

@article{context,
  title={Context-aware graph inference with knowledge distillation for visual dialog},
  author={Guo, Dan and Wang, Hui and Wang, Meng},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  volume={44},
  number={10},
  pages={6056--6073},
  year={2021},
  publisher={IEEE}
}

@inproceedings{dadnet,
  title={Dadnet: Dilated-attention-deformable convnet for crowd counting},
  author={Guo, Dan and Li, Kun and Zha, Zheng-Jun and Wang, Meng},
  booktitle={Proceedings of the 27th ACM international conference on multimedia},
  pages={1823--1832},
  year={2019}
}


@inproceedings{gan,
  author    = {Petar Velickovic and
               Guillem Cucurull and
               Arantxa Casanova and
               Adriana Romero and
               Pietro Li{\`{o}} and
               Yoshua Bengio},
  title     = {Graph Attention Networks},
  booktitle = {6th International Conference on Learning Representations, {ICLR} 2018,
               Vancouver, BC, Canada, April 30 - May 3, 2018, Conference Track Proceedings},
  publisher = {OpenReview.net},
  year      = {2018},
  url       = {https://openreview.net/forum?id=rJXMpikCZ},
  timestamp = {Thu, 25 Jul 2019 14:25:41 +0200},
  biburl    = {https://dblp.org/rec/conf/iclr/VelickovicCCRLB18.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{lmsar,
  author    = {Dingkang Yang and
               Haopeng Kuang and
               Shuai Huang and
               Lihua Zhang},
   title     = {Learning Modality-Specific and -Agnostic Representations for Asynchronous
               Multimodal Language Sequences},
  booktitle = {{MM} '22: The 30th {ACM} International Conference on Multimedia, Lisboa,
               Portugal, October 10 - 14, 2022},
  pages     = {1708--1717},
  publisher = {{ACM}},
  year      = {2022},
  url       = {https://doi.org/10.1145/3503161.3547755},
  doi       = {10.1145/3503161.3547755},
  timestamp = {Fri, 14 Oct 2022 14:25:06 +0200},
  biburl    = {https://dblp.org/rec/conf/mm/YangKHZ22.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{rod,
  author    = {Jianing Li and
               Xiao Wang and
               Lin Zhu and
               Jia Li and
               Tiejun Huang and
               Yonghong Tian},
  title     = {Retinomorphic Object Detection in Asynchronous Visual Streams},
  booktitle = {Thirty-Sixth {AAAI} Conference on Artificial Intelligence, {AAAI}
               2022, Virtual Event, February 22
               - March 1, 2022},
  pages     = {1332--1340},
  publisher = {{AAAI} Press},
  year      = {2022},
  url       = {https://ojs.aaai.org/index.php/AAAI/article/view/20021},
  timestamp = {Fri, 30 Dec 2022 23:08:52 +0100},
  biburl    = {https://dblp.org/rec/conf/aaai/LiW000022.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{hrnet,
  author    = {Ke Sun and
               Bin Xiao and
               Dong Liu and
               Jingdong Wang},
  title     = {Deep High-Resolution Representation Learning for Human Pose Estimation},
  booktitle = {{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
               2019, Long Beach, CA, USA, June 16-20, 2019},
  pages     = {5693--5703},
  publisher = {Computer Vision Foundation / {IEEE}},
  year      = {2019},
  url       = {http://openaccess.thecvf.com/content\_CVPR\_2019/html/Sun\_Deep\_High-Resolution\_Representation\_Learning\_for\_Human\_Pose\_Estimation\_CVPR\_2019\_paper.html},
  doi       = {10.1109/CVPR.2019.00584},
  timestamp = {Tue, 18 Oct 2022 08:35:28 +0200},
  biburl    = {https://dblp.org/rec/conf/cvpr/0009XLW19.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{grain,
  author    = {Wei Li and
               Tianzhao Yang and
               Xiao Wu and
               Zhaoquan Yuan},
  editor    = {Luc De Raedt},
  title     = {Learning Graph-based Residual Aggregation Network for Group Activity
               Recognition},
  booktitle = {Proceedings of the Thirty-First International Joint Conference on
               Artificial Intelligence, {IJCAI} 2022, Vienna, Austria, 23-29 July
               2022},
  pages     = {1102--1108},
  publisher = {ijcai.org},
  year      = {2022},
  url       = {https://doi.org/10.24963/ijcai.2022/154},
  doi       = {10.24963/ijcai.2022/154},
  timestamp = {Wed, 27 Jul 2022 16:43:00 +0200},
  biburl    = {https://dblp.org/rec/conf/ijcai/LiY0Y22.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@ARTICLE{icr,
title = {Investigating Causal Relations by Econometric Models and Cross-Spectral Methods},
author = {Granger, Clive},
year = {1969},
journal = {Econometrica},
volume = {37},
number = {3},
pages = {424-38},
url = {https://EconPapers.repec.org/RePEc:ecm:emetrp:v:37:y:1969:i:3:p:424-38}
}



@article{torvam,
  author    = {Elsa Siggiridou and
               Dimitris Kugiumtzis},
  title     = {Granger Causality in Multivariate Time Series Using a Time-Ordered
               Restricted Vector Autoregressive Model},
  journal   = {{IEEE} Trans. Signal Process.},
  volume    = {64},
  number    = {7},
  pages     = {1759--1773},
  year      = {2016},
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  doi       = {10.1109/TSP.2015.2500893},
  timestamp = {Tue, 10 Mar 2020 10:52:03 +0100},
  biburl    = {https://dblp.org/rec/journals/tsp/SiggiridouK16.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

	
@article{pc,
  author    = {Amy Sue Fire and
               Song{-}Chun Zhu},
  title     = {Learning Perceptual Causality from Video},
  journal   = {{ACM} Trans. Intell. Syst. Technol.},
  volume    = {7},
  number    = {2},
  pages     = {23:1--23:22},
  year      = {2016},
  url       = {https://doi.org/10.1145/2809782},
  doi       = {10.1145/2809782},
  timestamp = {Mon, 11 May 2020 15:53:31 +0200},
  biburl    = {https://dblp.org/rec/journals/tist/FireZ16.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
	
@inproceedings{tbct,
  author    = {Mark Edmonds and
               Xiaojian Ma and
               Siyuan Qi and
               Yixin Zhu and
               Hongjing Lu and
               Song{-}Chun Zhu},
  title     = {Theory-Based Causal Transfer: Integrating Instance-Level Induction
               and Abstract-Level Structure Learning},
  booktitle = {The Thirty-Fourth {AAAI} Conference on Artificial Intelligence, {AAAI}
               2020, New York, NY, USA,
               February 7-12, 2020},
  pages     = {1283--1291},
  publisher = {{AAAI} Press},
  year      = {2020},
  url       = {https://ojs.aaai.org/index.php/AAAI/article/view/5483},
  timestamp = {Mon, 07 Mar 2022 16:57:48 +0100},
  biburl    = {https://dblp.org/rec/conf/aaai/EdmondsMQZLZ20.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{acre,
  author    = {Chi Zhang and
               Baoxiong Jia and
               Mark Edmonds and
               Song{-}Chun Zhu and
               Yixin Zhu},
  title     = {{ACRE:} Abstract Causal REasoning Beyond Covariation},
  booktitle = {{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
               2021, virtual, June 19-25, 2021},
  pages     = {10643--10653},
  publisher = {Computer Vision Foundation / {IEEE}},
  year      = {2021},
  url       = {https://openaccess.thecvf.com/content/CVPR2021/html/Zhang\_ACRE\_Abstract\_Causal\_REasoning\_Beyond\_Covariation\_CVPR\_2021\_paper.html},
  doi       = {10.1109/CVPR46437.2021.01050},
  timestamp = {Mon, 18 Jul 2022 16:47:41 +0200},
  biburl    = {https://dblp.org/rec/conf/cvpr/0017JEZZ21.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{tgc,
  author    = {Irene Winkler and
               Danny Panknin and
               Daniel Bartz and
               Klaus{-}Robert M{\"{u}}ller and
               Stefan Haufe},
  title     = {Validity of Time Reversal for Testing Granger Causality},
  journal   = {{IEEE} Trans. Signal Process.},
  volume    = {64},
  number    = {11},
  pages     = {2746--2760},
  year      = {2016},
  url       = {https://doi.org/10.1109/TSP.2016.2531628},
  doi       = {10.1109/TSP.2016.2531628},
  timestamp = {Tue, 10 Mar 2020 10:50:52 +0100},
  biburl    = {https://dblp.org/rec/journals/tsp/WinklerPBMH16.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{dgc,
  author    = {Ribhu Chopra and
               Chandra Ramabhadra Murthy and
               Govindan Rangarajan},
  title     = {Statistical Tests for Detecting Granger Causality},
  journal   = {{IEEE} Trans. Signal Process.},
  volume    = {66},
  number    = {22},
  pages     = {5803--5816},
  year      = {2018},
  url       = {https://doi.org/10.1109/TSP.2018.2872004},
  doi       = {10.1109/TSP.2018.2872004},
  timestamp = {Tue, 10 Mar 2020 10:53:59 +0100},
  biburl    = {https://dblp.org/rec/journals/tsp/ChopraMR18.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{gcdahp,
  author    = {Gautam Bhattacharya and
               Koushik Ghosh and
               Ananda S. Chowdhury},
  title     = {Granger Causality Driven {AHP} for Feature Weighted kNN},
  journal   = {Pattern Recognit.},
  volume    = {66},
  pages     = {425--436},
  year      = {2017},
  url       = {https://doi.org/10.1016/j.patcog.2017.01.018},
  doi       = {10.1016/j.patcog.2017.01.018},
  timestamp = {Fri, 27 Mar 2020 08:35:16 +0100},
  biburl    = {https://dblp.org/rec/journals/pr/BhattacharyaGC17.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{stan,
  author    = {Mengyuan Liu and
               Youneng Bao and
               Yongsheng Liang and
               Fanyang Meng},
  title     = {Spatial-Temporal Asynchronous Normalization for Unsupervised 3D Action
               Representation Learning},
  journal   = {{IEEE} Signal Process. Lett.},
  volume    = {29},
  pages     = {632--636},
  year      = {2022},
  url       = {https://doi.org/10.1109/LSP.2022.3144898},
  doi       = {10.1109/LSP.2022.3144898},
  timestamp = {Fri, 01 Apr 2022 11:24:39 +0200},
  biburl    = {https://dblp.org/rec/journals/spl/LiuBLM22.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{astmn,
  author    = {Jianing Li and
               Jia Li and
               Lin Zhu and
               Xijie Xiang and
               Tiejun Huang and
               Yonghong Tian},
  title     = {Asynchronous Spatio-Temporal Memory Network for Continuous Event-Based
               Object Detection},
  journal   = {{IEEE} Trans. Image Process.},
  volume    = {31},
  pages     = {2975--2987},
  year      = {2022},
  url       = {https://doi.org/10.1109/TIP.2022.3162962},
  doi       = {10.1109/TIP.2022.3162962},
  timestamp = {Wed, 27 Apr 2022 20:11:56 +0200},
  biburl    = {https://dblp.org/rec/journals/tip/LiLZXHT22.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{atf,
  author    = {Gunnar A. Sigurdsson and
               Santosh Kumar Divvala and
               Ali Farhadi and
               Abhinav Gupta},
  title     = {Asynchronous Temporal Fields for Action Recognition},
  booktitle = {2017 {IEEE} Conference on Computer Vision and Pattern Recognition,
               {CVPR} 2017, Honolulu, HI, USA, July 21-26, 2017},
  pages     = {5650--5659},
  publisher = {{IEEE} Computer Society},
  year      = {2017},
  url       = {https://doi.org/10.1109/CVPR.2017.599},
  doi       = {10.1109/CVPR.2017.599},
  timestamp = {Wed, 16 Oct 2019 14:14:50 +0200},
  biburl    = {https://dblp.org/rec/conf/cvpr/SigurdssonDFG17.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{aia,
  author    = {Jiajun Tang and
               Jin Xia and
               Xinzhi Mu and
               Bo Pang and
               Cewu Lu},
  editor    = {Andrea Vedaldi and
               Horst Bischof and
               Thomas Brox and
               Jan{-}Michael Frahm},
  title     = {Asynchronous Interaction Aggregation for Action Detection},
  booktitle = {Computer Vision - {ECCV} 2020 - 16th European Conference, Glasgow,
               UK, August 23-28, 2020, Proceedings, Part {XV}},
  series    = {Lecture Notes in Computer Science},
  volume    = {12360},
  pages     = {71--87},
  publisher = {Springer},
  year      = {2020},
  url       = {https://doi.org/10.1007/978-3-030-58555-6\_5},
  doi       = {10.1007/978-3-030-58555-6\_5},
  timestamp = {Tue, 17 Nov 2020 16:51:25 +0100},
  biburl    = {https://dblp.org/rec/conf/eccv/TangXMPL20.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
@inproceedings{af,
  author    = {Weiyao Lin and
               Chongyang Zhang and
               Ke Lu and
               Bin Sheng and
               Jianxin Wu and
               Bingbing Ni and
               Xin Liu and
               Hongkai Xiong},
  editor    = {Sheila A. McIlraith and
               Kilian Q. Weinberger},
  title     = {Action Recognition With Coarse-to-Fine Deep Feature Integration and
               Asynchronous Fusion},
  booktitle = {Proceedings of the Thirty-Second {AAAI} Conference on Artificial Intelligence,
               (AAAI-18), New Orleans, Louisiana, USA, February
               2-7, 2018},
  pages     = {7130--7137},
  publisher = {{AAAI} Press},
  year      = {2018},
  url       = {https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16144},
  timestamp = {Tue, 08 Mar 2022 21:46:35 +0100},
  biburl    = {https://dblp.org/rec/conf/aaai/LinZLSWNLX18.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{mfi,
  author    = {Vibhav Vineet and
               Jonathan Warrell and
               Philip H. S. Torr},
  title     = {Filter-Based Mean-Field Inference for Random Fields with Higher-Order
               Terms and Product Label-Spaces},
  journal   = {Int. J. Comput. Vis.},
  volume    = {110},
  number    = {3},
  pages     = {290--307},
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  url       = {https://doi.org/10.1007/s11263-014-0708-6},
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  timestamp = {Fri, 13 Mar 2020 10:59:23 +0100},
  biburl    = {https://dblp.org/rec/journals/ijcv/VineetWT14.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{vc,
  author    = {Hangjie Yuan and
               Dong Ni},
  title     = {Learning Visual Context for Group Activity Recognition},
  booktitle = {Thirty-Fifth {AAAI} Conference on Artificial Intelligence, {AAAI}
               2021, Virtual Event, February 2-9,
               2021},
  pages     = {3261--3269},
  publisher = {{AAAI} Press},
  year      = {2021},
  url       = {https://ojs.aaai.org/index.php/AAAI/article/view/16437},
  timestamp = {Wed, 22 Sep 2021 15:21:50 +0200},
  biburl    = {https://dblp.org/rec/conf/aaai/YuanN21.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{srnn,
  author    = {Sovan Biswas and
               Juergen Gall},
  title     = {Structural Recurrent Neural Network {(SRNN)} for Group Activity Analysis},
  booktitle = {2018 {IEEE} Winter Conference on Applications of Computer Vision,
               {WACV} 2018, Lake Tahoe, NV, USA, March 12-15, 2018},
  pages     = {1625--1632},
  publisher = {{IEEE} Computer Society},
  year      = {2018},
  url       = {https://doi.org/10.1109/WACV.2018.00180},
  doi       = {10.1109/WACV.2018.00180},
  timestamp = {Wed, 16 Oct 2019 14:14:49 +0200},
  biburl    = {https://dblp.org/rec/conf/wacv/BiswasG18.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{saacrf,
  author    = {Rizard Renanda Adhi Pramono and
               Wen{-}Hsien Fang and
               Yie{-}Tarng Chen},
  title     = {Relational Reasoning for Group Activity Recognition via Self-Attention
               Augmented Conditional Random Field},
  journal   = {{IEEE} Trans. Image Process.},
  volume    = {30},
  pages     = {8184--8199},
  year      = {2021},
  url       = {https://doi.org/10.1109/TIP.2021.3113570},
  doi       = {10.1109/TIP.2021.3113570},
  timestamp = {Tue, 05 Oct 2021 10:02:17 +0200},
  biburl    = {https://dblp.org/rec/journals/tip/PramonoFC21.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@article{fcar,
  author    = {Peizhen Zhang and
               Yongyi Tang and
               Jianfang Hu and
               Wei{-}Shi Zheng},
  title     = {Fast Collective Activity Recognition Under Weak Supervision},
  journal   = {{IEEE} Trans. Image Process.},
  volume    = {29},
  pages     = {29--43},
  year      = {2020},
  url       = {https://doi.org/10.1109/TIP.2019.2918725},
  doi       = {10.1109/TIP.2019.2918725},
  timestamp = {Sat, 30 May 2020 19:55:16 +0200},
  biburl    = {https://dblp.org/rec/journals/tip/ZhangTHZ20.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{arg,
	title = {Learning Actor Relation Graphs for Group Activity Recognition},
	author = {Jianchao Wu and Limin Wang and Li Wang and Jie Guo and Gangshan Wu},
	booktitle = {CVPR},
	year = {2019},
}

@inproceedings{maskrcnn,
	title={Mask r-cnn},
	author={He, Kaiming and Gkioxari, Georgia and Doll{\'a}r, Piotr and Girshick, Ross},
	booktitle={Proceedings of the IEEE international conference on computer vision},
	pages={2961--2969},
	year={2017}
}

@article{dfc,
	author = {Liu, Jichao and Wang, Chuanxu and Gong, Yuting and Hao, Xue},
	year = {2019},
	month = {07},
	pages = {1-1},
	title = {Deep Fully Connected Model For Collective Activity Recognition},
	volume = {PP},
	journal = {IEEE Access},
	doi = {10.1109/ACCESS.2019.2929684}
}

@book{pmh,
	title={Group Activity Recognition via Computing Human Pose Motion History and Collective Map from Video},
	author={ Chen, H. Y.  and  Lai, S. H. },
	publisher={Pattern Recognition},
	year={2020},
}

@article{mdl,
	title={Multimodal Deep Learning for Group Activity Recognition in Smart Office Environments},
	author={ Florea, G. A.  and  Mihailescu, R. C. },
	journal={Future Internet},
	volume={12},
	number={8},
	pages={133},
	year={2020},
}

@book{hrn,
	title={Hierarchical Relational Networks for Group Activity Recognition and Retrieval: 15th European Conference, Munich, Germany, September 8–14, 2018, Proceedings, Part III},
	author={ Ibrahim, M. S.  and  Mori, G. },
	publisher={Computer Vision – ECCV 2018},
	year={2018},
}

@inproceedings{hdn,
	title={Hierarchical Deep Network for Group Discovery and Multi-level Activity Recognition},
	author={Goyal, Ashish and Bhargava, Neha and Chaudhuri, Subhasis and Velmurugan, Rajbabu},
	booktitle={Proceedings of the 11th Indian Conference on Computer Vision, Graphics and Image Processing},
	pages={1--7},
	year={2018}
}

@inproceedings{hacm,
	title={Hierarchical Attention and Context Modeling for Group Activity Recognition},
	author={ Kong, L.  and  Jie, Q.  and  Di, H.  and  Wang, Y.  and  Gool, L. V. },
	booktitle={ICASSP 2018 - 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
	year={2018},
}

@inproceedings{sbgar,
	title={SBGAR: Semantics Based Group Activity Recognition},
	author={ Xin, L.  and  Chuah, M. C. },
	booktitle={IEEE International Conference on Computer Vision},
	year={2017},
}

@inproceedings{rmic,
	title={Recurrent Modeling of Interaction Context for Collective Activity Recognition},
	author={ Wang, M.  and  Ni, B.  and  Yang, X. },
	booktitle={2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
	year={2017},
}

@inproceedings{sim,
	title={Structure Inference Machines: Recurrent Neural Networks for Analyzing Relations in Group Activity Recognition},
	author={ Deng, Z.  and  Vahdat, A.  and  Hu, H.  and  Mori, G. },
	booktitle={2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
	year={2016},
}

@inproceedings{hdtm,
	title={A Hierarchical Deep Temporal Model for Group Activity Recognition},
	author={ Ibrahim, M.  and  Muralidharan, S.  and  Deng, Z.  and  Vahdat, A.  and  Mori, G. },
	booktitle={2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
	year={2016},
}

@article{dsm,
	title={Deep Structured Models For Group Activity Recognition},
	author={ Deng, Z.  and  Zhai, M.  and  Chen, L.  and  Liu, Y.  and  Muralidharan, S.  and  Roshtkhari, M. J.  and  Mori, G. },
	journal={The British Machine Vision Conference (BMVC)},
	year={2015},
}

@inproceeings{micpk,
	title={Visual recognition by counting instances: A multi-instance cardinality potential kernel},
	author={ Hajimirsadeghi, H.  and  Yan, W.  and  Vahdat, A.  and  Mori, G. },
	booktitle={2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
	year={2015},
}

@inproceedings{lc,
	title={Learning context for collective activity recognition},
	author={ Choi, W.  and  Shahid, K.  and  Savarese, S. },
	booktitle={Computer Vision and Pattern Recognition},
	year={2011},
}

@article{Kong2018,
	title={Human Action Recognition and Prediction: A Survey},
	author={ Kong, Y.  and  Fu, Y. },
	year={2018},
}

@inproceedings{Liu2020,
	title={Grouped Temporal Enhancement Module for Human Action Recognition},
	author={ Liu, H.  and  Ren, B.  and  Liu, M.  and  Ding, R. },
	booktitle={2020 IEEE International Conference on Image Processing (ICIP)},
	year={2020},
}

@inproceedings{prl,
	title={Progressive Relation Learning for Group Activity Recognition},
	author={ Hu, G.  and  Cui, B.  and  He, Y.  and  Yu, S. },
	booktitle={2020 {IEEE/CVF} Conference on Computer Vision and Pattern Recognition,
               {CVPR} 2020, Seattle, WA, USA, June 13-19, 2020},
	year={2020},
}

@book{pdar,
	title={Group Activity Recognition by Exploiting Position Distribution and Appearance Relation},
	author={ Pei, D.  and  Li, A.  and  Wang, Y. },
	publisher={MultiMedia Modeling, 27th International Conference, MMM 2021, Prague, Czech Republic, June 22–24, 2021, Proceedings, Part I},
	year={2021},
}

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	title={A comprehensive survey on graph neural networks},
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	publisher={IEEE}
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@article{dlm,
	title={Discriminative Latent Models for Recognizing Contextual Group Activities},
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@inproceedings{arn,
	title={Attentive relational networks for mapping images to scene graphs},
	author={Qi, Mengshi and Li, Weijian and Yang, Zhengyuan and Wang, Yunhong and Luo, Jiebo},
	booktitle={{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
               2019, Long Beach, CA, USA, June 16-20, 2019},
	pages={3957--3966},
	year={2019}
}

@inproceedings{tsagcn,
	title={Two-stream adaptive graph convolutional networks for skeleton-based action recognition},
	author={Shi, Lei and Zhang, Yifan and Cheng, Jian and Lu, Hanqing},
	booktitle={{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
               2019, Long Beach, CA, USA, June 16-20, 2019},
	pages={12026--12035},
	year={2019}
}

@inproceedings{hooi,
	title={Attend and interact: Higher-order object interactions for video understanding},
	author={Ma, Chih-Yao and Kadav, Asim and Melvin, Iain and Kira, Zsolt and AlRegib, Ghassan and Graf, Hans Peter},
	booktitle={2018 {IEEE} Conference on Computer Vision and Pattern Recognition,
               {CVPR} 2018, Salt Lake City, UT, USA, June 18-22, 2018},
	pages={6790--6800},
	year={2018}
}

@inproceedings{acrn,
	title={Actor-centric relation network},
	author={Sun, Chen and Shrivastava, Abhinav and Vondrick, Carl and Murphy, Kevin and Sukthankar, Rahul and Schmid, Cordelia},
	booktitle={Computer Vision - {ECCV} 2018 - 15th European Conference, Munich,
               Germany, September 8-14, 2018, Proceedings, Part {XI}},
	pages={318--334},
	year={2018}
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@inproceedings{inception-v3,
  author    = {Christian Szegedy and
               Vincent Vanhoucke and
               Sergey Ioffe and
               Jonathon Shlens and
               Zbigniew Wojna},
  title     = {Rethinking the Inception Architecture for Computer Vision},
  booktitle = {2016 {IEEE} Conference on Computer Vision and Pattern Recognition,
               {CVPR} 2016, Las Vegas, NV, USA, June 27-30, 2016},
  pages     = {2818--2826},
  publisher = {{IEEE} Computer Society},
  year      = {2016},
  url       = {https://doi.org/10.1109/CVPR.2016.308},
  doi       = {10.1109/CVPR.2016.308},
  timestamp = {Sun, 25 Oct 2020 23:02:11 +0100},
  biburl    = {https://dblp.org/rec/conf/cvpr/SzegedyVISW16.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
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@inproceedings{inception-v4,
	title={Inception-v4, inception-resnet and the impact of residual connections on learning},
	author={Szegedy, Christian and Ioffe, Sergey and Vanhoucke, Vincent and Alemi, Alexander},
	booktitle={Proceedings of the Thirty-First {AAAI} Conference on Artificial Intelligence,
               February 4-9, 2017, San Francisco, California, {USA}},
    pages     = {4278--4284},
	year={2017}
}

@article{ldcm,
	author = {Zhao, Chaoyang and Wang, Jinqiao and Lu, Hanqing},
	year = {2017},
	month = {03},
	pages = {1-20},
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	volume = {76},
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@inproceedings{sam,
	title={Social adaptive module for weakly-supervised group activity recognition},
	author={Yan, Rui and Xie, Lingxi and Tang, Jinhui and Shu, Xiangbo and Tian, Qi},
	booktitle={Computer Vision - {ECCV} 2020 - 16th European Conference, Glasgow,
               UK, August 23-28, 2020, Proceedings, Part {VIII}},
	pages={208--224},
	year={2020},
	organization={Springer}
}

@inproceedings{etsfg,
	title={Efficient Temporal-Spatial Feature Grouping For Video Action Recognition},
	author={Qiu, Zhikang and Zhao, Xu and Hu, Zhilan},
	booktitle={2020 IEEE International Conference on Image Processing (ICIP)},
	pages={2176--2180},
	year={2020},
	organization={IEEE}
}

@article{glil,
	title={Host-parasite: Graph LSTM-in-LSTM for group activity recognition},
	author={Shu, Xiangbo and Zhang, Liyan and Sun, Yunlian and Tang, Jinhui},
	journal={IEEE transactions on neural networks and learning systems},
	year={2020},
	publisher={IEEE}
}


@inproceedings{mlir,
	title={Learning Multi-level Interaction Relations and Feature Representations for Group Activity Recognition},
	author={Lu, Lihua and Lu, Yao and Wang, Shunzhou},
	booktitle={International Conference on Multimedia Modeling},
	pages={617--628},
	year={2021},
	organization={Springer}
}

@article{gaim,
	title={GAIM: Graph Attention based Interaction Model for Collective Activity Recognition},
	author={ Lu, L.  and  Yu, R.  and  Di, H.  and  Zhang, L.  and  Lu, Y. },
	journal={IEEE Transactions on Multimedia},
	volume={PP},
	number={99},
	pages={1-1},
	year={2019},
}

@article{ccglstm,
  author    = {Jinhui Tang and
               Xiangbo Shu and
               Rui Yan and
               Liyan Zhang},
  title     = {Coherence Constrained Graph {LSTM} for Group Activity Recognition},
  journal   = {{IEEE} Trans. Pattern Anal. Mach. Intell.},
  volume    = {44},
  number    = {2},
  pages     = {636--647},
  year      = {2022},
  url       = {https://doi.org/10.1109/TPAMI.2019.2928540},
  doi       = {10.1109/TPAMI.2019.2928540},
  timestamp = {Tue, 16 Aug 2022 17:12:06 +0200},
  biburl    = {https://dblp.org/rec/journals/pami/TangSYZ22.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
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	title={CERN: confidence-energy recurrent network for group activity recognition},
	author={Shu, Tianmin and Todorovic, Sinisa and Zhu, Song-Chun},
	booktitle={2017 {IEEE} Conference on Computer Vision and Pattern Recognition,
               {CVPR} 2017, Honolulu, HI, USA, July 21-26, 2017},
	pages={5523--5531},
	year={2017}
}

@article{santoro2017simple,
	title={A simple neural network module for relational reasoning},
	author={Santoro, Adam and Raposo, David and Barrett, David GT and Malinowski, Mateusz and Pascanu, Razvan and Battaglia, Peter and Lillicrap, Timothy},
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	year={2017}
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@inproceedings{deka,
	title={Detecting events and key actors in multi-person videos},
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               {CVPR} 2016, Las Vegas, NV, USA, June 27-30, 2016},
	pages={3043--3053},
	year={2016}
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@inproceedings{tsn,
	title={Temporal segment networks: Towards good practices for deep action recognition},
	author={Wang, Limin and Xiong, Yuanjun and Wang, Zhe and Qiao, Yu and Lin, Dahua and Tang, Xiaoou and Van Gool, Luc},
	booktitle={Computer Vision - {ECCV} 2016 - 14th European Conference, Amsterdam,
               The Netherlands, October 11-14, 2016, Proceedings, Part {VIII}},
	pages={20--36},
	year={2016},
	organization={Springer}
}

@inproceedings{hirf,
	title={Hirf: Hierarchical random field for collective activity recognition in videos},
	author={Amer, Mohamed Rabie and Lei, Peng and Todorovic, Sinisa},
	booktitle={Computer Vision - {ECCV} 2014 - 13th European Conference, Zurich,
               Switzerland, September 6-12, 2014, Proceedings, Part {VI}},
	pages={572--585},
	year={2014},
	organization={Springer}
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@article{uca,
	title={Understanding collective activities of people from videos},
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	journal={IEEE transactions on pattern analysis and machine intelligence},
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	publisher={IEEE}
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@inproceedings{mtt,
	title={A unified framework for multi-target tracking and collective activity recognition},
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               Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part {IV}},
	pages={215--230},
	year={2012},
	organization={Springer}
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@article{dlm,
	title={Discriminative latent models for recognizing contextual group activities},
	author={Lan, Tian and Wang, Yang and Yang, Weilong and Robinovitch, Stephen N and Mori, Greg},
	journal={IEEE transactions on pattern analysis and machine intelligence},
	volume={34},
	number={8},
	pages={1549--1562},
	year={2011},
	publisher={IEEE}
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@inproceedings{strap,
	title={What are they doing?: Collective activity classification using spatio-temporal relationship among people},
	author={Choi, Wongun and Shahid, Khuram and Savarese, Silvio},
	booktitle={12th {IEEE} International Conference on Computer Vision Workshops,
               {ICCV} Workshops 2009, Kyoto, Japan, September 27 - October 4, 2009},
	pages={1282--1289},
	year={2009},
	organization={IEEE}
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@article{pbgcn,
	title={Part-based graph convolutional network for action recognition},
	author={Thakkar, Kalpit and Narayanan, PJ},
	journal={arXiv preprint arXiv:1809.04983},
	year={2018}
}

@inproceedings{mlsgan,
	title={Multi-level sequence gan for group activity recognition},
	author={Gammulle, Harshala and Denman, Simon and Sridharan, Sridha and Fookes, Clinton},
	booktitle={Computer Vision - {ACCV} 2018 - 14th Asian Conference on Computer
               Vision, Perth, Australia, December 2-6, 2018, Revised Selected Papers,
               Part {I}},
	pages={331--346},
	year={2018},
	organization={Springer}
}

@article{man-trans,
	title={Memory attention networks for skeleton-based action recognition},
	author={Li, Ce and Xie, Chunyu and Zhang, Baochang and Han, Jungong and Zhen, Xiantong and Chen, Jie},
	journal={IEEE Transactions on Neural Networks and Learning Systems},
	year={2021},
	publisher={IEEE}
}

@article{acrn,
	title={Actor-Centric Relation Network},
	author={ Sun, C.  and  Shrivastava, A.  and  Vondrick, C.  and  Murphy, K.  and  Sukthankar, R.  and  Schmid, C. },
	journal={Springer, Cham},
	year={2018},
}

@inproceedings{man-ijcai,
	title={Memory Attention Networks for Skeleton-based Action Recognition},
	author={Xie, Chunyu and Li, Ce and Zhang, Baochang and Chen, Chen and Han, Jungong and Liu, Jianzhuang},
	booktitle={Proceedings of the Twenty-Seventh International Joint Conference on
               Artificial Intelligence, {IJCAI} 2018, July 13-19, 2018, Stockholm,
               Sweden},
	year={2018}
}

@inproceedings{rmic,
	title={Recurrent Modeling of Interaction Context for Collective Activity Recognition},
	author={ Wang, M.  and  Ni, B.  and  Yang, X. },
	booktitle={2017 {IEEE} Conference on Computer Vision and Pattern Recognition,
               {CVPR} 2017, Honolulu, HI, USA, July 21-26, 2017},
	year={2017},
}

@inproceedings{srtsl,
	title={Skeleton-based action recognition with spatial reasoning and temporal stack learning},
	author={Si, Chenyang and Jing, Ya and Wang, Wei and Wang, Liang and Tan, Tieniu},
	booktitle={Computer Vision - {ECCV} 2018 - 15th European Conference, Munich,
               Germany, September 8-14, 2018, Proceedings, Part {I}},
	pages={103--118},
	year={2018}
}

@inproceedings{rpan,
	title={Rpan: An end-to-end recurrent pose-attention network for action recognition in videos},
	author={Du, Wenbin and Wang, Yali and Qiao, Yu},
	booktitle={{IEEE} International Conference on Computer Vision, {ICCV} 2017, Venice,
               Italy, October 22-29, 2017},
	pages={3725--3734},
	year={2017}
}

@inproceedings{ssu,
	title={Social scene understanding: End-to-end multi-person action localization and collective activity recognition},
	author={Bagautdinov, Timur and Alahi, Alexandre and Fleuret, Fran{\c{c}}ois and Fua, Pascal and Savarese, Silvio},
	booktitle={2017 {IEEE} Conference on Computer Vision and Pattern Recognition,
               {CVPR} 2017, Honolulu, HI, USA, July 21-26, 2017},
	pages={4315--4324},
	year={2017}
}

@inproceedings{far,
	title={Football action recognition using hierarchical lstm},
	author={Tsunoda, Takamasa and Komori, Yasuhiro and Matsugu, Masakazu and Harada, Tatsuya},
	booktitle={2017 {IEEE} Conference on Computer Vision and Pattern Recognition
               Workshops, {CVPR} Workshops 2017, Honolulu, HI, USA, July 21-26, 2017},
	pages={99--107},
	year={2017}
}

@inproceedings{stam,
	title={An end-to-end spatio-temporal attention model for human action recognition from skeleton data},
	author={Song, Sijie and Lan, Cuiling and Xing, Junliang and Zeng, Wenjun and Liu, Jiaying},
	booktitle={Proceedings of the Thirty-First {AAAI} Conference on Artificial Intelligence,
               February 4-9, 2017, San Francisco, California, {USA}},
	volume={31},
	number={1},
	year={2017}
}

@article{apool,
	title={Attentional pooling for action recognition},
	author={Girdhar, Rohit and Ramanan, Deva},
	journal={arXiv preprint arXiv:1711.01467},
	year={2017}
}

@inproceedings{sbgar,
	title={Sbgar: Semantics based group activity recognition},
	author={Li, Xin and Choo Chuah, Mooi},
	booktitle={{IEEE} International Conference on Computer Vision, {ICCV} 2017, Venice,
               Italy, October 22-29, 2017},
	pages={2876--2885},
	year={2017}
}

@article{videolstm,
	title={Videolstm convolves, attends and flows for action recognition},
	author={Li, Zhenyang and Gavrilyuk, Kirill and Gavves, Efstratios and Jain, Mihir and Snoek, Cees GM},
	journal={Computer Vision and Image Understanding},
	volume={166},
	pages={41--50},
	year={2018},
	publisher={Elsevier}
}

@inproceedings{dhoi,
	title={Learning to detect human-object interactions},
	author={Chao, Yu-Wei and Liu, Yunfan and Liu, Xieyang and Zeng, Huayi and Deng, Jia},
	booktitle={2018 {IEEE} Winter Conference on Applications of Computer Vision,
               {WACV} 2018, Lake Tahoe, NV, USA, March 12-15, 2018},
	pages={381--389},
	year={2018},
	organization={IEEE}
}

@inproceedings{fgbglg,
	title={Feature Grouping Based on Ga and L-Gem for Human Activity Recognition},
	author={Xue, Yi-Wen and Liu, Jing and Chen, Jiamin and Zhang, Yun-Tao and Cao, Renhua},
	booktitle={2018 International Conference on Machine Learning and Cybernetics,
               {ICMLC} 2018, Chengdu, China, July 15-18, 2018},
	volume={1},
	pages={44--49},
	year={2018},
	organization={IEEE}
}

@inproceedings{mspa,
	title={Mining semantics-preserving attention for group activity recognition},
	author={Tang, Yansong and Wang, Zian and Li, Peiyang and Lu, Jiwen and Yang, Ming and Zhou, Jie},
	booktitle={2018 {ACM} Multimedia Conference on Multimedia Conference, {MM} 2018,
               Seoul, Republic of Korea, October 22-26, 2018},
	pages={1283--1291},
	year={2018}
}

@article{hlstcm,
	title={Hierarchical long short-term concurrent memory for human interaction recognition},
	author={Shu, Xiangbo and Tang, Jinhui and Qi, Guojun and Liu, Wei and Yang, Jian},
	journal={IEEE transactions on pattern analysis and machine intelligence},
	year={2018},
	publisher={IEEE}
}

@inproceedings{gpnn,
	title={Learning human-object interactions by graph parsing neural networks},
	author={Qi, Siyuan and Wang, Wenguan and Jia, Baoxiong and Shen, Jianbing and Zhu, Song-Chun},
	booktitle={Computer Vision - {ECCV} 2018 - 15th European Conference, Munich,
               Germany, September 8-14, 2018, Proceedings, Part {IX}},
	pages={401--417},
	year={2018}
}

@inproceedings{stgcn,
	title={Spatial temporal graph convolutional networks for skeleton-based action recognition},
	author={Yan, Sijie and Xiong, Yuanjun and Lin, Dahua},
	booktitle={Proceedings of the Thirty-Second {AAAI} Conference on Artificial Intelligence,
               (AAAI-18), New Orleans, Louisiana, USA, February
               2-7, 2018},
	volume={32},
	number={1},
	year={2018}
}

@inproceedings{pctdm,
	title={Participation-contributed temporal dynamic model for group activity recognition},
	author={Yan, Rui and Tang, Jinhui and Shu, Xiangbo and Li, Zechao and Tian, Qi},
	booktitle={2018 {ACM} Multimedia Conference on Multimedia Conference, {MM} 2018,
               Seoul, Republic of Korea, October 22-26, 2018},
	pages={1292--1300},
	year={2018}
}

@article{gru,
	title={Discriminative context learning with gated recurrent unit for group activity recognition},
	author={Kim, Pil-Soo and Lee, Dong-Gyu and Lee, Seong-Whan},
	journal={Pattern Recognition},
	volume={76},
	pages={149--161},
	year={2018},
	publisher={Elsevier}
}


@inproceedings{gf,
	title={GroupFormer: Group Activity Recognition with Clustered Spatial-Temporal Transformer},
	author={Li, Shuaicheng and Cao, Qianggang and Liu, Lingbo and Yang, Kunlin and Liu, Shinan and Hou, Jun and Yi, Shuai},
	booktitle={2021 {IEEE/CVF} International Conference on Computer Vision, {ICCV}
               2021, Montreal, QC, Canada, October 10-17, 2021},
	pages={13668--13677},
	year={2021}
}

@inproceedings{din,
	title={Spatio-temporal dynamic inference network for group activity recognition},
	author={Yuan, Hangjie and Ni, Dong and Wang, Mang},
	booktitle={2021 {IEEE/CVF} International Conference on Computer Vision, {ICCV}
               2021, Montreal, QC, Canada, October 10-17, 2021},
	pages={7476--7485},
	year={2021}
}


@inproceedings{at,
	title={Actor-transformers for group activity recognition},
	author={Gavrilyuk, Kirill and Sanford, Ryan and Javan, Mehrsan and Snoek, Cees GM},
	booktitle={2020 {IEEE/CVF} Conference on Computer Vision and Pattern Recognition,
               {CVPR} 2020, Seattle, WA, USA, June 13-19, 2020},
	pages={839--848},
	year={2020}
}

@article{mmrr,
	title={Group activity recognition by using effective multiple modality relation representation with temporal-spatial attention},
	author={Xu, Dezhong and Fu, Heng and Wu, Lifang and Jian, Meng and Wang, Dong and Liu, Xu},
	journal={IEEE Access},
	volume={8},
	pages={65689--65698},
	year={2020},
	publisher={IEEE}
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@article{stva,
	title={Action recognition with spatio--temporal visual attention on skeleton image sequences},
	author={Yang, Zhengyuan and Li, Yuncheng and Yang, Jianchao and Luo, Jiebo},
	journal={IEEE Transactions on Circuits and Systems for Video Technology},
	volume={29},
	number={8},
	pages={2405--2415},
	year={2018},
	publisher={IEEE}
}

@inproceedings{tik,
	title={Transferable interactiveness knowledge for human-object interaction detection},
	author={Li, Yong-Lu and Zhou, Siyuan and Huang, Xijie and Xu, Liang and Ma, Ze and Fang, Hao-Shu and Wang, Yanfeng and Lu, Cewu},
	booktitle={{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
               2019, Long Beach, CA, USA, June 16-20, 2019},
	pages={3585--3594},
	year={2019}
}

@article{spaci,
	title={Learning semantics-preserving attention and contextual interaction for group activity recognition},
	author={Tang, Yansong and Lu, Jiwen and Wang, Zian and Yang, Ming and Zhou, Jie},
	journal={IEEE Transactions on Image Processing},
	volume={28},
	number={10},
	pages={4997--5012},
	year={2019},
	publisher={IEEE}
}

@inproceedings{lsta,
	title={Lsta: Long short-term attention for egocentric action recognition},
	author={Sudhakaran, Swathikiran and Escalera, Sergio and Lanz, Oswald},
	booktitle={{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
               2019, Long Beach, CA, USA, June 16-20, 2019},
	pages={9954--9963},
	year={2019}
}

@inproceedings{crm,
	title={Convolutional relational machine for group activity recognition},
	author={Azar, Sina Mokhtarzadeh and Atigh, Mina Ghadimi and Nickabadi, Ahmad and Alahi, Alexandre},
	booktitle={{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
               2019, Long Beach, CA, USA, June 16-20, 2019},
	pages={7892--7901},
	year={2019}
}

@inproceedings{lcgn,
	title={Language-conditioned graph networks for relational reasoning},
	author={Hu, Ronghang and Rohrbach, Anna and Darrell, Trevor and Saenko, Kate},
	booktitle={2019 {IEEE/CVF} International Conference on Computer Vision, {ICCV}
               2019, Seoul, Korea (South), October 27 - November 2, 2019},
	pages={10294--10303},
	year={2019}
}

@article{hpgnn,
	title={How powerful are graph neural networks?},
	author={Xu, Keyulu and Hu, Weihua and Leskovec, Jure and Jegelka, Stefanie},
	journal={arXiv preprint arXiv:1810.00826},
	year={2018}
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@inproceedings{aegclstm,
	title={An attention enhanced graph convolutional lstm network for skeleton-based action recognition},
	author={Si, Chenyang and Chen, Wentao and Wang, Wei and Wang, Liang and Tan, Tieniu},
	booktitle={{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
               2019, Long Beach, CA, USA, June 16-20, 2019},
	pages={1227--1236},
	year={2019}
}

@article{stagnet,
	title={stagNet: an attentive semantic RNN for group activity and individual action recognition},
	author={Qi, Mengshi and Wang, Yunhong and Qin, Jie and Li, Annan and Luo, Jiebo and Van Gool, Luc},
	journal={IEEE Transactions on Circuits and Systems for Video Technology},
	volume={30},
	number={2},
	pages={549--565},
	year={2019},
	publisher={IEEE}
}


@inproceedings{tik,
	title={Transferable interactiveness knowledge for human-object interaction detection},
	author={Li, Yong-Lu and Zhou, Siyuan and Huang, Xijie and Xu, Liang and Ma, Ze and Fang, Hao-Shu and Wang, Yanfeng and Lu, Cewu},
	booktitle={{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
               2019, Long Beach, CA, USA, June 16-20, 2019},
	pages={3585--3594},
	year={2019}
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@inproceedings{sg,
  author    = {Mahsa Ehsanpour and
               Alireza Abedin and
               Fatemeh Sadat Saleh and
               Javen Shi and
               Ian D. Reid and
               Hamid Rezatofighi},
  editor    = {Andrea Vedaldi and
               Horst Bischof and
               Thomas Brox and
               Jan{-}Michael Frahm},
  title     = {Joint Learning of Social Groups, Individuals Action and Sub-group
               Activities in Videos},
  booktitle = {Computer Vision - {ECCV} 2020 - 16th European Conference, Glasgow,
               UK, August 23-28, 2020, Proceedings, Part {IX}},
  series    = {Lecture Notes in Computer Science},
  volume    = {12354},
  pages     = {177--195},
  publisher = {Springer},
  year      = {2020},
  url       = {https://doi.org/10.1007/978-3-030-58545-7\_11},
  doi       = {10.1007/978-3-030-58545-7\_11},
  timestamp = {Tue, 10 Aug 2021 14:38:20 +0200},
  biburl    = {https://dblp.org/rec/conf/eccv/EhsanpourASSRR20.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
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@article{dirv,
	title={DIRV: Dense Interaction Region Voting for End-to-End Human-Object Interaction Detection},
	author={Fang, Hao-Shu and Xie, Yichen and Shao, Dian and Lu, Cewu},
	journal={arXiv preprint arXiv:2010.01005},
	year={2020}
}

@inproceedings{hoiduip,
	title={Learning human-object interaction detection using interaction points},
	author={Wang, Tiancai and Yang, Tong and Danelljan, Martin and Khan, Fahad Shahbaz and Zhang, Xiangyu and Sun, Jian},
	booktitle={2020 {IEEE/CVF} Conference on Computer Vision and Pattern Recognition,
               {CVPR} 2020, Seattle, WA, USA, June 13-19, 2020},
	pages={4116--4125},
	year={2020}
}

@inproceedings{ppdm,
	title={Ppdm: Parallel point detection and matching for real-time human-object interaction detection},
	author={Liao, Yue and Liu, Si and Wang, Fei and Chen, Yanjie and Qian, Chen and Feng, Jiashi},
	booktitle={2020 {IEEE/CVF} Conference on Computer Vision and Pattern Recognition,
               {CVPR} 2020, Seattle, WA, USA, June 13-19, 2020},
	pages={482--490},
	year={2020}
}

@inproceedings{cagn,
	title={Consistency-Aware Graph Network for Human Interaction Understanding},
	author={Wang, Zhenhua and Meng, Jiajun and Guo, Dongyan and Zhang, Jianhua and Shi, Javen Qinfeng and Chen, Shengyong},
	booktitle={2021 {IEEE/CVF} International Conference on Computer Vision, {ICCV}
               2021, Montreal, QC, Canada, October 10-17, 2021},
	pages={13369--13378},
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}

@inproceedings{lcgn,
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	author={Hu, Ronghang and Rohrbach, Anna and Darrell, Trevor and Saenko, Kate},
	booktitle={2019 {IEEE/CVF} International Conference on Computer Vision, {ICCV}
               2019, Seoul, Korea (South), October 27 - November 2, 2019},
	pages={10294--10303},
	year={2019}
}

@inproceedings{sgcn,
	title={Skeleton-based action recognition with shift graph convolutional network},
	author={Cheng, Ke and Zhang, Yifan and He, Xiangyu and Chen, Weihan and Cheng, Jian and Lu, Hanqing},
	booktitle={2020 {IEEE/CVF} Conference on Computer Vision and Pattern Recognition,
               {CVPR} 2020, Seattle, WA, USA, June 13-19, 2020},
	pages={183--192},
	year={2020}
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@inproceedings{tsagcn,
	title={Two-stream adaptive graph convolutional networks for skeleton-based action recognition},
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	booktitle={{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
               2019, Long Beach, CA, USA, June 16-20, 2019},
	pages={12026--12035},
	year={2019}
}

@inproceedings{stgcn,
	title={Spatial temporal graph convolutional networks for skeleton-based action recognition},
	author={Yan, Sijie and Xiong, Yuanjun and Lin, Dahua},
	booktitle={Proceedings of the Thirty-Second {AAAI} Conference on Artificial Intelligence,
               (AAAI-18), New Orleans, Louisiana, USA, February
               2-7, 2018},
	year={2018}
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	year={2018}
}

@inproceedings{gpnn,
	title={Learning human-object interactions by graph parsing neural networks},
	author={Qi, Siyuan and Wang, Wenguan and Jia, Baoxiong and Shen, Jianbing and Zhu, Song-Chun},
	booktitle={Computer Vision - {ECCV} 2018 - 15th European Conference, Munich,
               Germany, September 8-14, 2018, Proceedings, Part {IX}},
	pages={401--417},
	year={2018}
}

@inproceedings{nmp,
	title={Neural message passing for quantum chemistry},
	author={Gilmer, Justin and Schoenholz, Samuel S and Riley, Patrick F and Vinyals, Oriol and Dahl, George E},
	booktitle={Proceedings of the 34th International Conference on Machine Learning,
               {ICML} 2017, Sydney, NSW, Australia, 6-11 August 2017},
	pages={1263--1272},
	year={2017},
	organization={PMLR}
}

@article{irr,
	title={Communicative Message Passing for Inductive Relation Reasoning},
	author={Mai, Sijie and Zheng, Shuangjia and Yang, Yuedong and Hu, Haifeng},
	journal={arXiv preprint arXiv:2012.08911},
	year={2020}
}

@article{nri,
	title={Neural Relational Inference with Efficient Message Passing Mechanisms},
	author={Chen, Siyuan and Wang, Jiahai and Li, Guoqing},
	journal={arXiv preprint arXiv:2101.09486},
	year={2021}
}

@inproceedings{uhrl,
	title={Unsupervised Hyperbolic Representation Learning via Message Passing Auto-Encoders},
	author={Park, Jiwoong and Cho, Junho and Chang, Hyung Jin and Choi, Jin Young},
	booktitle={{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
               2021, virtual, June 19-25, 2021},
	pages={5516--5526},
	year={2021}
}

@inproceedings{rgnas,
	title={Rethinking Graph Neural Architecture Search from Message-passing},
	author={Cai, Shaofei and Li, Liang and Deng, Jincan and Zhang, Beichen and Zha, Zheng-Jun and Su, Li and Huang, Qingming},
	booktitle={{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
               2021, virtual, June 19-25, 2021},
	pages={6657--6666},
	year={2021}
}

@inproceedings{brepnet,
	title={BRepNet: A topological message passing system for solid models},
	author={Lambourne, Joseph G and Willis, Karl DD and Jayaraman, Pradeep Kumar and Sanghi, Aditya and Meltzer, Peter and Shayani, Hooman},
	booktitle={{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
               2021, virtual, June 19-25, 2021},
	pages={12773--12782},
	year={2021}
}

@article{dbtmp,
	title={Denoising-Based Turbo Message Passing for Compressed Video Background Subtraction},
	author={Xue, Zhipeng and Yuan, Xiaojun and Yang, Yang},
	journal={IEEE Transactions on Image Processing},
	volume={30},
	pages={2682--2696},
	year={2021},
	publisher={IEEE}
}

@inproceedings{bgn,
	title={Bipartite Graph Network with Adaptive Message Passing for Unbiased Scene Graph Generation},
	author={Li, Rongjie and Zhang, Songyang and Wan, Bo and He, Xuming},
	booktitle={{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
               2021, virtual, June 19-25, 2021},
	pages={11109--11119},
	year={2021}
}

@inproceedings{hhmp,
	title={Multi-modal Multi-label Emotion Recognition with Heterogeneous Hierarchical Message Passing},
	author={Zhang, Dong and Ju, Xincheng and Zhang, Wei and Li, Junhui and Li, Shoushan and Zhu, Qiaoming and Zhou, Guodong},
	booktitle={Thirty-Fifth {AAAI} Conference on Artificial Intelligence, {AAAI}
               2021, Virtual Event, February 2-9,
               2021},
	volume={35},
	number={16},
	pages={14338--14346},
	year={2021}
}

@article{sggmp,
	title={Scene-Graph-Guided message passing network for dense captioning},
	author={Liu, An-An and Wang, Yanhui and Xu, Ning and Liu, Shan and Li, Xuanya},
	journal={Pattern Recognition Letters},
	volume={145},
	pages={187--193},
	year={2021},
	publisher={Elsevier}
}

@inproceedings{hmpp,
	title={Hybrid Message Passing With Performance-Driven Structures for Facial Action Unit Detection},
	author={Song, Tengfei and Cui, Zijun and Zheng, Wenming and Ji, Qiang},
	booktitle={{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
               2021, virtual, June 19-25, 2021},
	pages={6267--6276},
	year={2021}
}

@article{fgnn,
	title={Factor graph neural network},
	author={Zhang, Zhen and Wu, Fan and Lee, Wee Sun},
	journal={arXiv preprint arXiv:1906.00554},
	year={2019}
}









