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Multi-person motion prediction remains a challenging problem, especially in the joint representation learning of individual motion and social interactions.
Discrete cosine transform
Ahmed, N.; Natarajan, T.; and Rao, K. R. 1974 · 1974
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Discrete cosine transform
Ahmed, N.; Natarajan, T.; and Rao, K. R. 1974 · 1974
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Long short-term memory
Hochreiter, S.; and Schmidhuber, J. 1997 · 1997
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Long short-term memory
Hochreiter, S.; and Schmidhuber, J. 1997 · 1997
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CMU Graphics Lab Motion Capture Database
CMU-Graphics-Lab. 2003 · 2003
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CMU Graphics Lab Motion Capture Database
CMU-Graphics-Lab. 2003 · 2003
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Attention, please: A spatio-temporal transformer for 3d human motion prediction
Aksan, E.; Cao, P.; Kaufmann, M.; and Hilliges, O. 2020 · 2004
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Attention, please: A spatio-temporal transformer for 3d human motion prediction
Aksan, E.; Cao, P.; Kaufmann, M.; and Hilliges, O. 2020 · 2004
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Gaussian process dynamical models for human motion
Wang, J. M.; Fleet, D. J.; and Hertzmann, A. 2007 · 2007
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Gaussian process dynamical models for human motion
Wang, J. M.; Fleet, D. J.; and Hertzmann, A. 2007 · 2007
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Umpm benchmark: A multi-person dataset with synchronized video and motion capture data for evaluation of articulated human motion and interaction
Van der Aa, N.; Luo, X.; Giezeman, G.-J.; Tan, R. T.; and Veltkamp, R. C. 2011 · 2011
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Umpm benchmark: A multi-person dataset with synchronized video and motion capture data for evaluation of articulated human motion and interaction
Van der Aa, N.; Luo, X.; Giezeman, G.-J.; Tan, R. T.; and Veltkamp, R. C. 2011 · 2011
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A generalization of transformer networks to graphs
Dwivedi, V. P.; and Bresson, X. 2020 · 2012
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A generalization of transformer networks to graphs
Dwivedi, V. P.; and Bresson, X. 2020 · 2012
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Efficient nonlinear markov models for human motion
Lehrmann, A. M.; Gehler, P. V.; and Nowozin, S. 2014 · 2014
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Efficient nonlinear markov models for human motion
Lehrmann, A. M.; Gehler, P. V.; and Nowozin, S. 2014 · 2014
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Recurrent network models for human dynamics
Fragkiadaki, K.; Levine, S.; Felsen, P.; and Malik, J. 2015 · 2015
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Social psychology: The study of human interaction
Newcomb, T. M.; Turner, R. H.; and Converse, P. E. 2015 · 2015
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Recurrent network models for human dynamics
Fragkiadaki, K.; Levine, S.; Felsen, P.; and Malik, J. 2015 · 2015
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Social psychology: The study of human interaction
Newcomb, T. M.; Turner, R. H.; and Converse, P. E. 2015 · 2015
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Social LSTM: Human Trajectory Prediction in Crowded Spaces
Alahi, A.; Goel, K.; Ramanathan, V.; Robicquet, A.; Fei-Fei, L.; and Savarese, S. 2016 · 2016
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Structural-rnn: Deep learning on spatio-temporal graphs
Jain, A.; Zamir, A. R.; Savarese, S.; and Saxena, A. 2016 · 2016
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Social LSTM: Human Trajectory Prediction in Crowded Spaces
Alahi, A.; Goel, K.; Ramanathan, V.; Robicquet, A.; Fei-Fei, L.; and Savarese, S. 2016 · 2016
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Structural-rnn: Deep learning on spatio-temporal graphs
Jain, A.; Zamir, A. R.; Savarese, S.; and Saxena, A. 2016 · 2016
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Attention is all you need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, Ł.; and Polosukhin, I. 2017 · 2017
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Attention is all you need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, Ł.; and Polosukhin, I. 2017 · 2017
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Hp-gan: Probabilistic 3d human motion prediction via gan
Barsoum, E.; Kender, J.; and Liu, Z. 2018 · 2018
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Adversarial geometry-aware human motion prediction
Gui, L.-Y.; Wang, Y.-X.; Liang, X.; and Moura, J. M. 2018 · 2018
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Neural Relational Inference for Interacting Systems
Kipf, T.; Fetaya, E.; Wang, K.-C.; Welling, M.; and Zemel, R. S. 2018 · 2018
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Single-shot multi-person 3d pose estimation from monocular rgb
Mehta, D.; Sotnychenko, O.; Mueller, F.; Xu, W.; Sridhar, S.; Pons-Moll, G.; and Theobalt, C. 2018 · 2018
Cited alongside, same era.
Recovering accurate 3d human pose in the wild using imus and a moving camera
Von Marcard, T.; Henschel, R.; Black, M. J.; Rosenhahn, B.; and Pons-Moll, G. 2018 · 2018
Cited alongside, same era.
Hp-gan: Probabilistic 3d human motion prediction via gan
Barsoum, E.; Kender, J.; and Liu, Z. 2018 · 2018
Cited alongside, same era.
Adversarial geometry-aware human motion prediction
Gui, L.-Y.; Wang, Y.-X.; Liang, X.; and Moura, J. M. 2018 · 2018
Cited alongside, same era.
Neural Relational Inference for Interacting Systems
Kipf, T.; Fetaya, E.; Wang, K.-C.; Welling, M.; and Zemel, R. S. 2018 · 2018
MSR-GCN: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction
Dang, L.; Nie, Y.; Long, C.; Zhang, Q.; and Li, G. 2021 · 2021
Later among the works it cites.
Edge-augmented Graph Transformers: Global Self-attention is Enough for Graphs
Hussain, M. S.; Zaki, M. J.; and Subramanian, D. 2021 · 2021
Later among the works it cites.
Multiscale spatio-temporal graph neural networks for 3d skeleton-based motion prediction
Li, M.; Chen, S.; Zhao, Y.; Zhang, Y.; Wang, Y.; and Tian, Q. 2021 · 2021
Later among the works it cites.
Activity graph transformer for temporal action localization
Nawhal, M.; and Mori, G. 2021 · 2021
Later among the works it cites.
Motion prediction via joint dependency modeling in phase space
Su, P.; Liu, Z.; Wu, S.; Zhu, L.; Yin, Y.; and Shen, X. 2021 · 2021
Later among the works it cites.
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Cited alongside, same era.
Single-shot multi-person 3d pose estimation from monocular rgb
Mehta, D.; Sotnychenko, O.; Mueller, F.; Xu, W.; Sridhar, S.; Pons-Moll, G.; and Theobalt, C. 2018 · 2018
Cited alongside, same era.
Recovering accurate 3d human pose in the wild using imus and a moving camera
Von Marcard, T.; Henschel, R.; Black, M. J.; Rosenhahn, B.; and Pons-Moll, G. 2018 · 2018
Cited alongside, same era.
Action-agnostic human pose forecasting
Chiu, H.-k.; Adeli, E.; Wang, B.; Huang, D.-A.; and Niebles, J. C. 2019 · 2019
Cited alongside, same era.
Stgat: Modeling spatial-temporal interactions for human trajectory prediction
Huang, Y.; Bi, H.; Li, Z.; Mao, T.; and Wang, Z. 2019 · 2019
Cited alongside, same era.
Bihmp-gan: Bidirectional 3d human motion prediction gan
Kundu, J. N.; Gor, M.; and Babu, R. V. 2019 · 2019
Cited alongside, same era.
Learning trajectory dependencies for human motion prediction
Mao, W.; Liu, M.; Salzmann, M.; and Li, H. 2019 · 2019
Cited alongside, same era.
Multi-Person 3D Motion Prediction with Multi-Range Transformers
Wang, J.; Xu, H.; Narasimhan, M.; and Wang, X. 2021 · 2021
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Rethinking and improving relative position encoding for vision transformer
Wu, K.; Peng, H.; Chen, M.; Fu, J.; and Chao, H. 2021 · 2021
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Knowledge-enhanced hierarchical graph transformer network for multi-behavior recommendation
Xia, L.; Huang, C.; Xu, Y.; Dai, P.; Zhang, X.; Yang, H.; Pei, J.; and Bo, L. 2021 · 2021
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Do transformers really perform badly for graph representation?
Ying, C.; Cai, T.; Luo, S.; Zheng, S.; Ke, G.; He, D.; Shen, Y.; and Liu, T.-Y. 2021 · 2021
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Agentformer: Agent-aware transformers for socio-temporal multi-agent forecasting
Yuan, Y.; Weng, X.; Ou, Y.; and Kitani, K. M. 2021 · 2021
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Tripod: Human trajectory and pose dynamics forecasting in the wild
Adeli, V.; Ehsanpour, M.; Reid, I.; Niebles, J. C.; Savarese, S.; Adeli, E.; and Rezatofighi, H. 2021 · 2021
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Towards accurate 3d human motion prediction from incomplete observations
Cui, Q.; and Sun, H. 2021 · 2021
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MSR-GCN: Multi-Scale Residual Graph Convolution Networks for Human Motion Prediction
Dang, L.; Nie, Y.; Long, C.; Zhang, Q.; and Li, G. 2021 · 2021
Later among the works it cites.
Edge-augmented Graph Transformers: Global Self-attention is Enough for Graphs
Hussain, M. S.; Zaki, M. J.; and Subramanian, D. 2021 · 2021
Later among the works it cites.
Multiscale spatio-temporal graph neural networks for 3d skeleton-based motion prediction
Li, M.; Chen, S.; Zhao, Y.; Zhang, Y.; Wang, Y.; and Tian, Q. 2021 · 2021
Later among the works it cites.
Activity graph transformer for temporal action localization
Nawhal, M.; and Mori, G. 2021 · 2021
Later among the works it cites.
Motion prediction via joint dependency modeling in phase space
Su, P.; Liu, Z.; Wu, S.; Zhu, L.; Yin, Y.; and Shen, X. 2021 · 2021
Later among the works it cites.
Multi-Person 3D Motion Prediction with Multi-Range Transformers
Wang, J.; Xu, H.; Narasimhan, M.; and Wang, X. 2021 · 2021
Later among the works it cites.
Rethinking and improving relative position encoding for vision transformer
Wu, K.; Peng, H.; Chen, M.; Fu, J.; and Chao, H. 2021 · 2021
Later among the works it cites.
Knowledge-enhanced hierarchical graph transformer network for multi-behavior recommendation
Xia, L.; Huang, C.; Xu, Y.; Dai, P.; Zhang, X.; Yang, H.; Pei, J.; and Bo, L. 2021 · 2021
Later among the works it cites.
Do transformers really perform badly for graph representation?
Ying, C.; Cai, T.; Luo, S.; Zheng, S.; Ke, G.; He, D.; Shen, Y.; and Liu, T.-Y. 2021 · 2021
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Agentformer: Agent-aware transformers for socio-temporal multi-agent forecasting
Yuan, Y.; Weng, X.; Ou, Y.; and Kitani, K. M. 2021 · 2021
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Multi-Person Extreme Motion Prediction
Guo, W.; Bie, X.; Alameda-Pineda, X.; and Moreno-Noguer, F. 2022 · 2022
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Semi-Supervised Classification with Graph Convolutional Networks
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GRPE: Relative Positional Encoding for Graph Transformer
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Multi-Person Extreme Motion Prediction
Guo, W.; Bie, X.; Alameda-Pineda, X.; and Moreno-Noguer, F. 2022 · 2022
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Semi-Supervised Classification with Graph Convolutional Networks
Kipf, T. N.; and Welling, M. 2022 · 2022
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GRPE: Relative Positional Encoding for Graph Transformer
Park, W.; Chang, W.-G.; Lee, D.; Kim, J.; et al. 2022 · 2022
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