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We present a novel method for populating 3D indoor scenes with virtual humans that can navigate in the environment and interact with objects in a realistic manner.
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Richard S Sutton and Andrew G Barto · 1998
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Simplified 3D movement and pathfinding using navigation meshes
Greg Snook · 2000
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Motion graphs
Lucas Kovar, Michael Gleicher, and Frédéric Pighin · 2008
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Sampling-based contact-rich motion control
Libin Liu, KangKang Yin, Michiel Van de Panne, Tianjia Shao, and Weiwei Xu · 2010
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What makes a chair a chair?
Helmut Grabner, Juergen Gall, and Luc Van Gool · 2011
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From 3d scene geometry to human workspace
Abhinav Gupta, Scott Satkin, Alexei A Efros, and Martial Hebert · 2011
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SceneGrok: Inferring action maps in 3D environments
Manolis Savva, Angel X Chang, Pat Hanrahan, Matthew Fisher, and Matthias Nießner · 2014
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Motion matching-the road to next gen animation
Michael Büttner and Simon Clavet · 2015
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Shapenet: An information-rich 3d model repository
Angel X Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, and Hao Su · 2015
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Improving sampling‐based motion control
Libin Liu, KangKang Yin, and Baining Guo · 2015
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A deep learning framework for character motion synthesis and editing
Daniel Holden, Jun Saito, and Taku Komura · 2016
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Scannet: Richly-annotated 3d reconstructions of indoor scenes
Angela Dai, Angel X. Chang, Manolis Savva, Maciej Halber, Thomas Funkhouser, and Matthias Nießner · 2017
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A recurrent variational autoencoder for human motion synthesis
Ikhsanul Habibie, Daniel Holden, Jonathan Schwarz, Joe Yearsley, and Taku Komura · 2017
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Phase-functioned neural networks for character control
Daniel Holden, Taku Komura, and Jun Saito · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Neural probabilistic motor primitives for humanoid control
Josh Merel, Leonard Hasenclever, Alexandre Galashov, Arun Ahuja, Vu Pham, Greg Wayne, Yee Whye Teh, and Nicolas Heess · 2018
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Deepmimic: Example-guided deep reinforcement learning of physics-based character skills
Xue Bin Peng, Pieter Abbeel, Sergey Levine, and Michiel Van de Panne · 2018
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Sfv: Reinforcement learning of physical skills from videos
Xue Bin Peng, Angjoo Kanazawa, Jitendra Malik, Pieter Abbeel, and Sergey Levine · 2018
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DReCon: data-driven responsive control of physics-based characters
Kevin Bergamin, Simon Clavet, Daniel Holden, and James Richard Forbes · 2019
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Machine learning for motion synthesis and character control in games
Michael Buttner · 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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Putting humans in a scene: Learning affordance in 3d indoor environments
Xueting Li, Sifei Liu, Kihwan Kim, Xiaolong Wang, Ming-Hsuan Yang, and Jan Kautz · 2019
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AMASS: Archive of motion capture as surface shapes
Naureen Mahmood, Nima Ghorbani, Nikolaus F Troje, Gerard Pons-Moll, and Michael J Black · 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 AA Osman, Dimitrios Tzionas, and Michael J Black · 2019
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Neural state machine for character-scene interactions
Sebastian Starke, He Zhang, Taku Komura, and Jun Saito · 2019
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The Replica dataset: A digital replica of indoor spaces
Julian Straub, Thomas Whelan, Lingni Ma, Yufan Chen, Erik Wijmans, Simon Green, Jakob J Engel, Raul Mur-Artal, Carl Ren, and Shobhit Verma · 2019
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PADL: Language-Directed Physics-Based Character Control
Jordan Juravsky, Yunrong Guo, Sanja Fidler, and Xue Bin Peng · 2022
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Ganimator: Neural motion synthesis from a single sequence
Peizhuo Li, Kfir Aberman, Zihan Zhang, Rana Hanocka, and Olga Sorkine-Hornung · 2022
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Ase: Large-scale reusable adversarial skill embeddings for physically simulated characters
Xue Bin Peng, Yunrong Guo, Lina Halper, Sergey Levine, and Sanja Fidler · 2022
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TEMOS: Generating diverse human motions from textual descriptions
Mathis Petrovich, Michael J Black, and Gül Varol · 2022
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Deepphase: Periodic autoencoders for learning motion phase manifolds
Sebastian Starke, Ian Mason, and Taku Komura · 2022
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Real-time controllable motion transition for characters
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Combining recurrent neural networks and adversarial training for human motion synthesis and control
Zhiyong Wang, Jinxiang Chai, and Shihong Xia · 2019
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Ml tutorial day: From motion matching to motion synthesis, and all the hurdles in between
Fabio Zinno · 2019
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Learned motion matching
Daniel Holden, Oussama Kanoun, Maksym Perepichka, and Tiberiu Popa · 2020
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Predictive and generative neural networks for object functionality
Ruizhen Hu, Zihao Yan, Jingwen Zhang, Oliver Van Kaick, Ariel Shamir, Hao Zhang, and Hui Huang · 2020
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Character controllers using motion vaes
Hung Yu Ling, Fabio Zinno, George Cheng, and Michiel Van De Panne · 2020
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Local motion phases for learning multi-contact character movements
Sebastian Starke, Yiwei Zhao, Taku Komura, and Kazi Zaman · 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
Cited alongside, same era.
Xiangjun Tang, He Wang, Bo Hu, Xu Gong, Ruifan Yi, Qilong Kou, and Xiaogang Jin · 2022
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Motionclip: Exposing human motion generation to clip space
Guy Tevet, Brian Gordon, Amir Hertz, Amit H Bermano, and Daniel Cohen-Or · 2022
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Guy Tevet, Sigal Raab, Brian Gordon, Yonatan Shafir, Daniel Cohen-Or, and Amit H Bermano · 2022
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EDGE: Editable Dance Generation From Music
Jonathan Tseng, Rodrigo Castellon, and C Karen Liu · 2022
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Towards diverse and natural scene-aware 3d human motion synthesis
Jingbo Wang, Yu Rong, Jingyuan Liu, Sijie Yan, Dahua Lin, and Bo Dai · 2022
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PhysDiff: Physics-Guided Human Motion Diffusion Model
Ye Yuan, Jiaming Song, Umar Iqbal, Arash Vahdat, and Jan Kautz · 2022
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Couch: towards controllable human-chair interactions
Xiaohan Zhang, Bharat Lal Bhatnagar, Sebastian Starke, Vladimir Guzov, and Gerard Pons-Moll · 2022
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The wanderings of odysseus in 3D scenes
Yan Zhang and Siyu Tang · 2022
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Compositional human-scene interaction synthesis with semantic control
Kaifeng Zhao, Shaofei Wang, Yan Zhang, Thabo Beeler, and Siyu Tang · 2022
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Gimo: Gaze-informed human motion prediction in context
Yang Zheng, Yanchao Yang, Kaichun Mo, Jiaman Li, Tao Yu, Yebin Liu, C Karen Liu, and Leonidas J Guibas · 2022
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Listen, denoise, action! audio-driven motion synthesis with diffusion models
Simon Alexanderson, Rajmund Nagy, Jonas Beskow, and Gustav Eje Henter · 2023
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GestureDiffuCLIP: Gesture diffusion model with CLIP latents
Tenglong Ao, Zeyi Zhang, and Libin Liu · 2023
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Synthesizing Physical Character-Scene Interactions, Feb. 2023
Mohamed Hassan, Yunrong Guo, Tingwu Wang, Michael Black, Sanja Fidler, and Xue Bin Peng · 2023
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Example-based Motion Synthesis via Generative Motion Matching
Weiyu Li, Xuelin Chen, Peizhuo Li, Olga Sorkine-Hornung, and Baoquan Chen · 2023
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CALM: Conditional Adversarial Latent Models for Directable Virtual Characters
Chen Tessler, Yoni Kasten, Yunrong Guo, Shie Mannor, Gal Chechik, and Xue Bin Peng · 2023
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Learning Physically Simulated Tennis Skills from Broadcast Videos
Haotian Zhang, Ye Yuan, Viktor Makoviychuk, Yunrong Guo, Sanja Fidler, Xue Bin Peng, and Kayvon Fatahalian · 2023
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