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Digital human motion synthesis is a vibrant research field with applications in movies, AR/VR, and video games.
Learning structured output representation using deep conditional generative models
K. Sohn, H. Lee, and X. Yan · 2015
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On human motion prediction using recurrent neural networks
J. Martinez, M.J. Black, and J. Romero · 2017
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A simple yet effective baseline for 3d human pose estimation
J. Martinez, R. Hossain, J. Romero, and J.J. Little · 2017
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Embodied hands: Modeling and capturing hands and bodies together
J. Romero, D. Tzionas, and M.J. Black · 2017
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Attention is all you need
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A.N. Gomez, L. Kaiser, and I. Polosukhin · 2017
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Longterm human motion prediction by modeling motion context and enhancing motion dynamics
Y. Tang, L. Ma, W. Liu, and W. Zheng · 2018
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ContactGrasp: Functional Multi-finger Grasp Synthesis from Contact
S. Brahmbhatt, A. Handa, J. Hays, and D. Fox · 2019
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A neural temporal model for human motion prediction
A. Gopalakrishnan, A. Mali, D. Kifer, L. Giles, and A.G. Ororbia · 2019
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Putting humans in a scene: Learning affordance in 3d indoor environments
X. Li, S. Liu, K. Kim, X. Wang, M.H. Yang, and J. Kautz · 2019
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AMASS: Archive of motion capture as surface shapes
N. Mahmood, N. Ghorbani, N. F. Troje, G. Pons-Moll, and M. J. Black · 2019
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Overcoming limitations of mixture density networks: A sampling and fitting framework for multimodal future prediction
O. Makansi, E. Ilg, O. Cicek, and T. Brox · 2019
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Occupancy flow: 4d reconstruction by learning particle dynamics
M. Niemeyer, L. Mescheder, M. Oechsle, and A. Geiger · 2019
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Expressive body capture: 3D hands, face, and body from a single image
G. Pavlakos, V. Choutas, N. Ghorbani, T. Bolkart, A.A.A. Osman, D. Tzionas, and M.J. Black · 2019
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Efficient learning on point clouds with basis point sets
S. Prokudin, C. Lassner, and J Romero · 2019
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Sophie: An attentive gan for predicting paths compliant to social and physical constraints
A. Sadeghian, V. Kosaraju, A. Sadeghian, N. Hirose, H. Rezatofighi, and S. Savarese · 2019
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Neural state machine for characterscene interactions
S. Starke, H. Zhang, T. Komura, and J. Saito · 2019
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On the continuity of rotation representations in neural networks
Y. Zhou, C. Barnes, J. Lu, J. Yang, and H. Li · 2019
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A unified 3d human motion synthesis model via conditional variational auto-encoder
Y. Cai, Y. Wang, Y. Zhu, T.J. Cham, J. Cai, J. Yuan, J. Liu, C. Zheng, S. Yan, H. Ding, and et al · 2020
Cited alongside, same era.
Long-term human motion prediction with scene context
Z. Cao, H. Gao, K. Mangalam, Q.Z. Cai, M. Vo, and J. Malik · 2020
Cited alongside, same era.
Context-aware human motion prediction
E. Corona, A. Pumarola, G. Alenya, and F. Moreno-Noguer · 2020
Cited alongside, same era.
Robust motion inbetweening
F.G. Harvey, M. Yurick, D. Nowrouzezahrai, and C. Pal · 2020
Cited alongside, same era.
Grasping field: Learning implicit representations for human grasps
K. Karunratanakul, J. Yang, Y. Zhang, M.J. Black, K. Muandet, and S. Tang · 2020
Cited alongside, same era.
Convolutional autoencoders for human motion infilling
M. Kaufmann, E. Aksan, J. Song, F. Pece, R. Ziegler, and O. Hilliges · 2020
Ai choreographer: Music conditioned 3d dance generation with aist++
R. Li, S. Yang, D.A. Ross, and A. Kanazawa · 2021
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Action-conditioned 3d human motion synthesis with transformer vae
M. Petrovich, M.J. Black, and G. Varol · 2021
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D-nerf: Neural radiance fields for dynamic scenes
A. Pumarola, E. Corona, G. Pons-Moll, and F Moreno-Noguer · 2021
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Humor: 3d human motion model for robust pose estimation
D. Rempe, T. Birdal, A. Hertzmann, J. Yang, S. Sridhar, and L.J. Guibas · 2021
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Adversarial generation of continuous images
I. Skorokhodov, S. Ignatyev, and M. Elhoseiny · 2021
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Synthesizing long-term 3d human motion and interaction in 3d scenes
J. Wang, H. Xu, J. Xu, S. Liu, and X. Wang · 2021
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Cited alongside, same era.
History repeats itself: Human motion prediction via motion attention
W. Mao, M. Liu, and M. Salzmann · 2020
Cited alongside, same era.
Nerf: Representing scenes as neural radiance fields for view synthesis
B. Mildenhall, P.P. Srinivasan, M. Tancik, J.T. Barron, R. Ramamoorthi, and R. Ng · 2020
Cited alongside, same era.
Implicit neural representations with periodic activation functions
V. Sitzmann, J.N.P. Martel, A.W. Bergman, D.B. Lindell, and G Wetzstein · 2020
Cited alongside, same era.
GRAB: A dataset of whole-body human grasping of objects
O. Taheri, N. Ghorbani, M.J. Black, and D. Tzionas · 2020
Cited alongside, same era.
Dlow: Diversifying latent flows for diverse human motion prediction
Y. Yuan and K. Kitani · 2020
Cited alongside, same era.
Generating 3d people in scenes without people
Y. Zhang, M. Hassan, H. Neumann, M.J. Black, and S. Tang · 2020
Cited alongside, same era.
Manipnet: neural manipulation synthesis with a hand-object spatial representation
H. Zhang, Y. Ye, T. Shiratori, and T. Komura · 2021
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Learning motion priors for 4d human body capture in 3d scenes
S. Zhang, Y. Zhang, F. Bogo, M. Pollefeys, and S. Tang · 2021
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D-grasp: Physically plausible dynamic grasp synthesis for hand-object interactions
S. Christen, M. Kocabas, E. Aksan, J. Hwangbo, J. Song, and O. Hilliges · 2022
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NeMF: Neural motion fields for kinematic animation
C. He, J. Saito, J. Zachary, H. Rushmeier, and Y. Zhou · 2022
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Neural 3d video synthesis from multi-view video
T. Li, M. Slavcheva, M. Zollhöfer, S. Green, C. Lassner, C. Kim, T. Schmidt, S. Lovegrove, M. Goesele, R. Newcombe, and Z. Lv · 2022
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GOAL: Generating 4D whole-body motion for hand-object grasping
O. Taheri, V. Choutas, M.J. Black, and D. Tzionas · 2022
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Grasp’d: Differentiable contact-rich grasp synthesis for multi-fingered hands
D. Turpin, L. Wang, E. Heiden, Y. Chen, M. Macklin, S. Tsogkas, S. Dickinson, and A. Garg · 2022
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Towards diverse and natural scene-aware 3d human motion synthesis
J. Wang, Y. Rong, J. Liu, S. Yan, D. Lin, and B. Dai · 2022
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SAGA: Stochastic whole-body grasping with contact
Y. Wu, J. Wang, Y. Zhang, S. Zhang, O. Hilliges, F. Yu, and S. Tang · 2022
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Generating videos with dynamics-aware implicit generative adversarial networks
S. Yu, J. Tack, S. Mo, H. Kim, J. Kim, J. Ha, and J. Shin · 2022
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Imos: Intent-driven full-body motion synthesis for human-object interactions
A. Ghosh, R. Dabral, V. Golyanik, C. Theobalt, and P. Slusallek · 2023
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