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We propose CG-HOI, the first method to address the task of generating dynamic 3D human-object interactions (HOIs) from text.
Interaction capture and synthesis
Paul G. Kry and Dinesh K. Pai · 2006
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Recurrent network models for human dynamics
Katerina Fragkiadaki, Sergey Levine, Panna Felsen, and Jitendra Malik · 2015
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SMPL: a skinned multi-person linear model
Matthew Loper, Naureen Mahmood, Javier Romero, Gerard Pons-Moll, and Michael J. Black · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Structural-rnn: Deep learning on spatio-temporal graphs
Ashesh Jain, Amir R. Zamir, Silvio Savarese, and Ashutosh Saxena · 2016
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On human motion prediction using recurrent neural networks
Julieta Martinez, Michael J. Black, and Javier Romero · 2017
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Pointnet: Deep learning on point sets for 3d classification and segmentation
Charles Ruizhongtai Qi, Hao Su, Kaichun Mo, and Leonidas J. Guibas · 2017
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Embodied hands: modeling and capturing hands and bodies together
Javier Romero, Dimitrios Tzionas, and Michael J. Black · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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HP-GAN: probabilistic 3d human motion prediction via GAN
Emad Barsoum, John R. Kender, and Zicheng Liu · 2018
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Accurate and diverse sampling of sequences based on a ”best of many” sample objective
Apratim Bhattacharyya, Bernt Schiele, and Mario Fritz · 2018
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Flexible neural representation for physics prediction
Damian Mrowca, Chengxu Zhuang, Elias Wang, Nick Haber, Li Fei-Fei, Josh Tenenbaum, and Daniel L. K. Yamins · 2018
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Long-term human motion prediction by modeling motion context and enhancing motion dynamics
Yongyi Tang, Lin Ma, Wei Liu, and Wei-Shi Zheng · 2018
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MT-VAE: learning motion transformations to generate multimodal human dynamics
Xinchen Yan, Akash Rastogi, Ruben Villegas, Kalyan Sunkavalli, Eli Shechtman, Sunil Hadap, Ersin Yumer, and Honglak Lee · 2018
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Object-oriented dynamics predictor
Guangxiang Zhu, Zhiao Huang, and Chongjie Zhang · 2018
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Structured prediction helps 3d human motion modelling
Emre Aksan, Manuel Kaufmann, and Otmar Hilliges · 2019
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Action-agnostic human pose forecasting
Hsu-Kuang Chiu, Ehsan Adeli, Borui Wang, De-An Huang, and Juan Carlos Niebles · 2019
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A neural temporal model for human motion prediction
Anand Gopalakrishnan, Ankur Arjun Mali, Dan Kifer, C. Lee Giles, and Alexander G. Ororbia II · 2019
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Resolving 3d human pose ambiguities with 3d scene constraints
Mohamed Hassan, Vasileios Choutas, Dimitrios Tzionas, and Michael J. Black · 2019
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Learning trajectory dependencies for human motion prediction
Wei Mao, Miaomiao Liu, Mathieu Salzmann, and Hongdong Li · 2019
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Expressive body capture: 3d hands, face, and body from a single image
Georgios Pavlakos, Vasileios Choutas, Nima Ghorbani, Timo Bolkart, Ahmed A. A. Osman, Dimitrios Tzionas, and Michael J. Black · 2019
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On the continuity of rotation representations in neural networks
Yi Zhou, Connelly Barnes, Jingwan Lu, Jimei Yang, and Hao Li · 2019
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A stochastic conditioning scheme for diverse human motion prediction
Mohammad Sadegh Aliakbarian, Fatemeh Sadat Saleh, Mathieu Salzmann, Lars Petersson, and Stephen Gould · 2020
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Long-term human motion prediction with scene context
Zhe Cao, Hang Gao, Karttikeya Mangalam, Qi-Zhi Cai, Minh Vo, and Jitendra Malik · 2020
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Action2motion: Conditioned generation of 3d human motions
Chuan Guo, Xinxin Zuo, Sen Wang, Shihao Zou, Qingyao Sun, Annan Deng, Minglun Gong, and Li Cheng · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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History repeats itself: Human motion prediction via motion attention
Wei Mao, Miaomiao Liu, and Mathieu Salzmann · 2020
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Predicting the physical dynamics of unseen 3d objects
Davis Rempe, Srinath Sridhar, He Wang, and Leonidas J. Guibas · 2020
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Dlow: Diversifying latent flows for diverse human motion prediction
Ye Yuan and Kris Kitani · 2020
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PLACE: proximity learning of articulation and contact in 3d environments
Siwei Zhang, Yan Zhang, Qianli Ma, Michael J. Black, and Siyu Tang · 2020
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Contactopt: Optimizing contact to improve grasps
Patrick Grady, Chengcheng Tang, Christopher D. Twigg, Minh Vo, Samarth Brahmbhatt, and Charles C. Kemp · 2021
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Stochastic scene-aware motion prediction
Mohamed Hassan, Duygu Ceylan, Ruben Villegas, Jun Saito, Jimei Yang, Yi Zhou, and Michael J. Black · 2021
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Populating 3d scenes by learning human-scene interaction
Mohamed Hassan, Partha Ghosh, Joachim Tesch, Dimitrios Tzionas, and Michael J. Black · 2021
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Hand-object contact consistency reasoning for human grasps generation
Hanwen Jiang, Shaowei Liu, Jiashun Wang, and Xiaolong Wang · 2021
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Generating smooth pose sequences for diverse human motion prediction
Wei Mao, Miaomiao Liu, and Mathieu Salzmann · 2021
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Action-conditioned 3d human motion synthesis with transformer VAE
Mathis Petrovich, Michael J. Black, and Gül Varol · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever · 2021
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
Cited alongside, same era.
Synthesizing long-term 3d human motion and interaction in 3d scenes
Jiashun Wang, Huazhe Xu, Jingwei Xu, Sifei Liu, and Xiaolong Wang · 2021
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Scene-aware generative network for human motion synthesis
Humanmac: Masked motion completion for human motion prediction
Ling-Hao Chen, Jiawei Zhang, Yewen Li, Yiren Pang, Xiaobo Xia, and Tongliang Liu · 2023
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Executing your commands via motion diffusion in latent space
Xin Chen, Biao Jiang, Wen Liu, Zilong Huang, Bin Fu, Tao Chen, and Gang Yu · 2023
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Diffupose: Monocular 3d human pose estimation via denoising diffusion probabilistic model
Jeongjun Choi, Dongseok Shim, and H. Jin Kim · 2023
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Mofusion: A framework for denoising-diffusion-based motion synthesis
Rishabh Dabral, Muhammad Hamza Mughal, Vladislav Golyanik, and Christian Theobalt · 2023
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Imos: Intent-driven full-body motion synthesis for human-object interactions
Anindita Ghosh, Rishabh Dabral, Vladislav Golyanik, Christian Theobalt, and Philipp Slusallek · 2023
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Synthesizing physical character-scene interactions
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Jingbo Wang, Sijie Yan, Bo Dai, and Dahua Lin · 2021
Cited alongside, same era.
We are more than our joints: Predicting how 3d bodies move
Yan Zhang, Michael J. Black, and Siyu Tang · 2021
Cited alongside, same era.
BEHAVE: dataset and method for tracking human object interactions
Bharat Lal Bhatnagar, Xianghui Xie, Ilya A. Petrov, Cristian Sminchisescu, Christian Theobalt, and Gerard Pons-Moll · 2022
Cited alongside, same era.
Forecasting characteristic 3d poses of human actions
Christian Diller, Thomas A. Funkhouser, and Angela Dai · 2022
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Learning multi-object dynamics with compositional neural radiance fields
Danny Driess, Zhiao Huang, Yunzhu Li, Russ Tedrake, and Marc Toussaint · 2022
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Generating diverse and natural 3d human motions from text
Chuan Guo, Shihao Zou, Xinxin Zuo, Sen Wang, Wei Ji, Xingyu Li, and Li Cheng · 2022
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Planning with diffusion for flexible behavior synthesis
Michael Janner, Yilun Du, Joshua B. Tenenbaum, and Sergey Levine · 2022
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Mohamed Hassan, Yunrong Guo, Tingwu Wang, Michael J. Black, Sanja Fidler, and Xue Bin Peng · 2023
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Diffusion-based generation, optimization, and planning in 3d scenes
Siyuan Huang, Zan Wang, Puhao Li, Baoxiong Jia, Tengyu Liu, Yixin Zhu, Wei Liang, and Song-Chun Zhu · 2023
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Full-body articulated human-object interaction
Nan Jiang, Tengyu Liu, Zhexuan Cao, Jieming Cui, Zhiyuan Zhang, Yixin Chen, He Wang, Yixin Zhu, and Siyuan Huang · 2023
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Placing human animations into 3d scenes by learning interaction- and geometry-driven keyframes
James F. Mullen Jr., Divya Kothandaraman, Aniket Bera, and Dinesh Manocha · 2023
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GMD: controllable human motion synthesis via guided diffusion models
Korrawe Karunratanakul, Konpat Preechakul, Supasorn Suwajanakorn, and Siyu Tang · 2023
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FLAME: free-form language-based motion synthesis & editing
Jihoon Kim, Jiseob Kim, and Sungjoon Choi · 2023
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NIFTY: neural object interaction fields for guided human motion synthesis
Nilesh Kulkarni, Davis Rempe, Kyle Genova, Abhijit Kundu, Justin Johnson, David Fouhey, and Leonidas J. Guibas · 2023
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Locomotion-action-manipulation: Synthesizing human-scene interactions in complex 3d environments
Jiye Lee and Hanbyul Joo · 2023
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Sigal Raab, Inbal Leibovitch, Guy Tevet, Moab Arar, Amit H. Bermano, and Daniel Cohen-Or · 2023
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Trace and pace: Controllable pedestrian animation via guided trajectory diffusion
Davis Rempe, Zhengyi Luo, Xue Bin Peng, Ye Yuan, Kris Kitani, Karsten Kreis, Sanja Fidler, and Or Litany · 2023
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Diffusion motion: Generate text-guided 3d human motion by diffusion model
Zhiyuan Ren, Zhihong Pan, Xin Zhou, and Le Kang · 2023
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Human motion diffusion as a generative prior
Yonatan Shafir, Guy Tevet, Roy Kapon, and Amit H. Bermano · 2023
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Towards globally consistent stochastic human motion prediction via motion diffusion
Jiarui Sun and Girish Chowdhary · 2023
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FLEX: full-body grasping without full-body grasps
Purva Tendulkar, Dídac Surís, and Carl Vondrick · 2023
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Human motion diffusion model
Guy Tevet, Sigal Raab, Brian Gordon, Yonatan Shafir, Daniel Cohen-Or, and Amit Haim Bermano · 2023
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Sibo Tian, Minghui Zheng, and Xiao Liang · 2023
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Fg-t2m: Fine-grained text-driven human motion generation via diffusion model
Yin Wang, Zhiying Leng, Frederick W. B. Li, Shun-Cheng Wu, and Xiaohui Liang · 2023
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Human joint kinematics diffusion-refinement for stochastic motion prediction
Dong Wei, Huaijiang Sun, Bin Li, Jianfeng Lu, Weiqing Li, Xiaoning Sun, and Shengxiang Hu · 2023
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Unified human-scene interaction via prompted chain-of-contacts
Zeqi Xiao, Tai Wang, Jingbo Wang, Jinkun Cao, Wenwei Zhang, Bo Dai, Dahua Lin, and Jiangmiao Pang · 2023
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Hierarchical planning and control for box loco-manipulation
Zhaoming Xie, Jonathan Tseng, Sebastian Starke, Michiel van de Panne, and C. Karen Liu · 2023
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Stochastic multi-person 3d motion forecasting
Sirui Xu, Yu-Xiong Wang, and Liangyan Gui · 2023
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Synthesizing long-term human motions with diffusion models via coherent sampling
Zhao Yang, Bing Su, and Ji-Rong Wen · 2023
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Affordance diffusion: Synthesizing hand-object interactions
Yufei Ye, Xueting Li, Abhinav Gupta, Shalini De Mello, Stan Birchfield, Jiaming Song, Shubham Tulsiani, and Sifei Liu · 2023
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Scannet++: A high-fidelity dataset of 3d indoor scenes
Chandan Yeshwanth, Yueh-Cheng Liu, Matthias Nießner, and Angela Dai · 2023
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Physdiff: Physics-guided human motion diffusion model
Ye Yuan, Jiaming Song, Umar Iqbal, Arash Vahdat, and Jan Kautz · 2023
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Remodiffuse: Retrieval-augmented motion diffusion model
Mingyuan Zhang, Xinying Guo, Liang Pan, Zhongang Cai, Fangzhou Hong, Huirong Li, Lei Yang, and Ziwei Liu · 2023
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Synthesizing diverse human motions in 3d indoor scenes
Kaifeng Zhao, Yan Zhang, Shaofei Wang, Thabo Beeler, and Siyu Tang · 2023
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CAMS: canonicalized manipulation spaces for category-level functional hand-object manipulation synthesis
Juntian Zheng, Qingyuan Zheng, Lixing Fang, Yun Liu, and Li Yi · 2023
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