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Recent advances in text-to-motion generation using diffusion and autoregressive models have shown promising results.
The KIT motion-language dataset
Matthias Plappert, Christian Mandery, and Tamim Asfour · 2016
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Neural discrete representation learning
Aäron van den Oord, Oriol Vinyals, and Koray Kavukcuoglu · 2017
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Language2pose: Natural language grounded pose forecasting
Chaitanya Ahuja and Louis-Philippe Morency · 2019
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Mask-predict: Parallel decoding of conditional masked language models
Marjan Ghazvininejad, Omer Levy, Yinhan Liu, and Luke Zettlemoyer · 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
Earlier work this paper cites.
Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, T. J. Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeff Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
Earlier work this paper cites.
Taming transformers for high-resolution image synthesis
Patrick Esser, Robin Rombach, and Björn Ommer · 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 P. Abbeel · 2020
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Glancing transformer for non-autoregressive neural machine translation
Lihua Qian, Hao Zhou, Yu Bao, Mingxuan Wang, Lin Qiu, Weinan Zhang, Yong Yu, and Lei Li · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Hierarchical quantized autoencoders
Will Williams, Sam Ringer, Tom Ash, John Hughes, David Macleod, and Jamie Dougherty · 2020
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Synthesis of compositional animations from textual descriptions
Anindita Ghosh, Noshaba Cheema, Cennet Oguz, Christian Theobalt, and P. Slusallek · 2021
Earlier work this paper cites.
Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen · 2021
Cited alongside, same era.
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
Cited alongside, same era.
Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Robin Rombach, A. Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
Cited alongside, same era.
Vector-quantized image modeling with improved vqgan
Jiahui Yu, Xin Li, Jing Yu Koh, Han Zhang, Ruoming Pang, James Qin, Alexander Ku, Yuanzhong Xu, Jason Baldridge, and Yonghui Wu · 2021
Edge: Editable dance generation from music
Jo-Han Tseng, Rodrigo Castellon, and C. Karen Liu · 2022
Later among the works it cites.
Motiondiffuse: Text-driven human motion generation with diffusion model
Mingyuan Zhang, Zhongang Cai, Liang Pan, Fangzhou Hong, Xinying Guo, Lei Yang, and Ziwei Liu · 2022
Later among the works it cites.
Motiongpt: Human motion as a foreign language
Biao Jiang, Xin Chen, Wen Liu, Jingyi Yu, Gang Yu, and Tao Chen · 2023
Closest in time.
Gmd: Controllable human motion synthesis via guided diffusion models
Korrawe Karunratanakul, Konpat Preechakul, Supasorn Suwajanakorn, and Siyu Tang · 2023
Closest in time.
Priority-centric human motion generation in discrete latent space
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Cited alongside, same era.
Maskgit: Masked generative image transformer
Huiwen Chang, Han Zhang, Lu Jiang, Ce Liu, and William T. Freeman · 2022
Cited alongside, same era.
Executing your commands via motion diffusion in latent space
Xin Chen, Biao Jiang, Wen Liu, Zilong Huang, Bin Fu, Tao Chen, Jingyi Yu, and Gang Yu · 2022
Cited alongside, same era.
Cogview2: Faster and better text-to-image generation via hierarchical transformers
Ming Ding, Wendi Zheng, Wenyi Hong, and Jie Tang · 2022
Cited alongside, same era.
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
Cited alongside, same era.
Imagen video: High definition video generation with diffusion models
Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang, Ruiqi Gao, Alexey A. Gritsenko, Diederik P. Kingma, Ben Poole, Mohammad Norouzi, David J. Fleet, and Tim Salimans · 2022
Cited alongside, same era.
Flame: Free-form language-based motion synthesis & editing
Jihoon Kim, Jiseob Kim, and Sungjoon Choi · 2022
Cited alongside, same era.
Temos: Generating diverse human motions from textual descriptions
Mathis Petrovich, Michael J. Black, and Gül Varol · 2022
Cited alongside, same era.
Hanyang Kong, Kehong Gong, Dongze Lian, Michael Bi Mi, and Xinchao Wang · 2023
Closest in time.
Diversemotion: Towards diverse human motion generation via discrete diffusion
Yunhong Lou, Linchao Zhu, Yaxiong Wang, Xiaohan Wang, and Yezhou Yang · 2023
Closest in time.
Tmr: Text-to-motion retrieval using contrastive 3d human motion synthesis
Mathis Petrovich, Michael J. Black, and Gül Varol · 2023
Closest in time.
Human motion diffusion as a generative prior
Yonatan Shafir, Guy Tevet, Roy Kapon, and Amit H. Bermano · 2023
Closest in time.
Controllable motion diffusion model
Yi Shi, Jingbo Wang, Xuekun Jiang, and Bo Dai · 2023
Closest in time.
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
Closest in time.
Omnicontrol: Control any joint at any time for human motion generation
Yiming Xie, Varun Jampani, Lei Zhong, Deqing Sun, and Huaizu Jiang · 2023
Closest in time.
Cross-modal retrieval for motion and text via doptriple loss
Sheng Yan, Yang Liu, Haoqiang Wang, Xin Du, Mengyuan Liu, and Hong Liu · 2023
Closest in time.
Generating human motion from textual descriptions with discrete representations
Jianrong Zhang, Yangsong Zhang, Xiaodong Cun, Shaoli Huang, Yong Zhang, Hongwei Zhao, Hongtao Lu, and Xiaodong Shen · 2023
Closest in time.
Attt2m: Text-driven human motion generation with multi-perspective attention mechanism
Chongyang Zhong, Lei Hu, Zihao Zhang, and Shihong Xia · 2023
Closest in time.