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In this paper, we present TMR, a simple yet effective approach for text to 3D human motion retrieval.
Motion graphs
Lucas Kovar, Michael Gleicher, and Frédéric H. Pighin · 2002
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Implicit probabilistic models of human motion for synthesis and tracking
H. Sidenbladh, M. J. Black, and L. Sigal · 2002
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Motion synthesis from annotations
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The KIT motion-language dataset
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Angela S Lin, Lemeng Wu, Rodolfo Corona, Kevin Tai, Qixing Huang, and Raymond J Mooney · 2018
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Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Language2Pose: Natural language grounded pose forecasting
Chaitanya Ahuja and Louis-Philippe Morency · 2019
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Temporal localization of moments in video collections with natural language
Victor Escorcia, Mattia Soldan, Josef Sivic, Bernard Ghanem, and Bryan Russell · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 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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DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf · 2019
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Convolutional sequence generation for skeleton-based action synthesis
Sijie Yan, Zhizhong Li, Yuanjun Xiong, Huahan Yan, and Dahua Lin · 2019
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Skeleton-aware networks for deep motion retargeting
Kfir Aberman, Peizhuo Li, Dani Lischinski, Olga Sorkine-Hornung, Daniel Cohen-Or, and Baoquan Chen · 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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Learned motion matching
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TVR: A large-scale dataset for video-subtitle moment retrieval
Jie Lei, Licheng Yu, Tamara L Berg, and Mohit Bansal · 2020
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MPNet: Masked and permuted pre-training for language understanding
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Nikos Athanasiou, Mathis Petrovich, Michael J. Black, and Gül Varol · 2022
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A motion matching-based framework for controllable gesture synthesis from speech
Ikhsanul Habibie, Mohamed Elgharib, Kripashindu Sarkar, Ahsan Abdullah, Simbarashe Nyatsanga, Michael Neff, and Christian Theobalt · 2022
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Sai Shashank Kalakonda, Shubh Maheshwari, Sarvadevabhatla, and Ravi Kiran · 2022
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BLIP: bootstrapping language-image pre-training for unified vision-language understanding and generation
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MPNet: Masked and permuted pre-training for language understanding
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Neural pose transfer by spatially adaptive instance normalization
Jiashun Wang, Chao Wen, Yanwei Fu, Haitao Lin, Tianyun Zou, Xiangyang Xue, and Yinda Zhang · 2020
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Perpetual motion: Generating unbounded human motion
Yan Zhang, Michael J. Black, and Siyu Tang · 2020
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Bayesian adversarial human motion synthesis
Rui Zhao, Hui Su, and Qiang Ji · 2020
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Frozen in time: A joint video and image encoder for end-to-end retrieval
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Synthesis of compositional animations from textual descriptions
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CLIP4Clip: An empirical study of CLIP for end to end video clip retrieval and captioning
Huaishao Luo, Lei Ji, Ming Zhong, Yang Chen, Wen Lei, Nan Duan, and Tianrui Li · 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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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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MAD: A scalable dataset for language grounding in videos from movie audio descriptions
Mattia Soldan, Alejandro Pardo, Juan León Alcázar, Fabian Caba, Chen Zhao, Silvio Giancola, and Bernard Ghanem · 2022
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LocATe: End-to-end localization of actions in 3D with transformers
Jiankai Sun, Bolei Zhou, Michael J. Black, and Arjun Chandrasekaran · 2022
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CoCa: Contrastive captioners are image-text foundation models
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When and why vision-language models behave like bags-of-words, and what to do about it?
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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
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SINC: Spatial composition of 3D human motions for simultaneous action generation
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Teaching structured vision & language concepts to vision & language models
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MultiAct: Long-term 3D human motion generation from multiple action labels
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T2M-GPT: Generating human motion from textual descriptions with discrete representations
Jianrong Zhang, Yangsong Zhang, Xiaodong Cun, Shaoli Huang, Yong Zhang, Hongwei Zhao, Hongtao Lu, and Xi Shen · 2023
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