Fetching the paper…
Reading the bibliography…
The scaling law has been validated in various domains, such as natural language processing (NLP) and massive computer vision tasks; however, its application to motion generation remains largely unexplored.
Scaling to very very large corpora for natural language disambiguation
Michele Banko and Eric Brill · 2001
Earlier work this paper cites.
Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
Earlier work this paper cites.
The kit motion-language dataset
Matthias Plappert, Christian Mandery, and Tamim Asfour · 2016
Earlier work this paper cites.
Deep learning scaling is predictable, empirically
Joel Hestness, Sharan Narang, Newsha Ardalani, Gregory Diamos, Heewoo Jun, Hassan Kianinejad, Md Mostofa Ali Patwary, Yang Yang, and Yanqi Zhou · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Text2action: Generative adversarial synthesis from language to action
Hyemin Ahn, Timothy Ha, Yunho Choi, Hwiyeon Yoo, and Songhwai Oh · 2018
Earlier work this paper cites.
Human motion modeling using dvgans
Xiao Lin and Mohamed R Amer · 2018
Earlier work this paper cites.
Learning a bidirectional mapping between human whole-body motion and natural language using deep recurrent neural networks
Matthias Plappert, Christian Mandery, and Tamim Asfour · 2018
Earlier work this paper cites.
Language2pose: Natural language grounded pose forecasting
Chaitanya Ahuja and Louis-Philippe Morency · 2019
Earlier work this paper cites.
Beyond human-level accuracy: Computational challenges in deep learning
Joel Hestness, Newsha Ardalani, and Gregory Diamos · 2019
Earlier work this paper cites.
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, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeff Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Ma teusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
Earlier work this paper cites.
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
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Earlier work this paper cites.
Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei · 2020
Earlier work this paper cites.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu · 2020
Earlier work this paper cites.
Text2gestures: A transformer-based network for generating emotive body gestures for virtual agents
Uttaran Bhattacharya, Nicholas Rewkowski, Abhishek Banerjee, Pooja Guhan, Aniket Bera, and Dinesh Manocha · 2021
Earlier work this paper cites.
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, et al · 2021
Earlier work this paper cites.
Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
Earlier work this paper cites.
Teach: Temporal action composition for 3d humans
Nikos Athanasiou, Mathis Petrovich, Michael J Black, and Gül Varol · 2022
Earlier work this paper cites.
Training compute-optimal large language models
Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de Las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, et al · 2022
Cited alongside, same era.
Avatarclip: Zero-shot text-driven generation and animation of 3d avatars
Fangzhou Hong, Mingyuan Zhang, Liang Pan, Zhongang Cai, Lei Yang, and Ziwei Liu · 2022
Cited alongside, same era.
Real-time style modelling of human locomotion via feature-wise transformations and local motion phases
Ian Mason, Sebastian Starke, and Taku Komura · 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.
Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Cited alongside, same era.
Motionlcm: Real-time controllable motion generation via latent consistency model
Wenxun Dai, Ling-Hao Chen, Jingbo Wang, Jinpeng Liu, Bo Dai, and Yansong Tang · 2024
Closest in time.
Momask: Generative masked modeling of 3d human motions
Chuan Guo, Yuxuan Mu, Muhammad Gohar Javed, Sen Wang, and Li Cheng · 2024
Closest in time.
Amd: Autoregressive motion diffusion
Bo Han, Hao Peng, Minjing Dong, Yi Ren, Yixuan Shen, and Chang Xu · 2024
Closest in time.
Stablemofusion: Towards robust and efficient diffusion-based motion generation framework
Yiheng Huang, Hui Yang, Chuanchen Luo, Yuxi Wang, Shibiao Xu, Zhaoxiang Zhang, Man Zhang, and Junran Peng · 2024
Closest in time.
Motiongpt: Human motion as a foreign language
Biao Jiang, Xin Chen, Wen Liu, Jingyi Yu, Gang Yu, and Tao Chen · 2024
Closest in time.
Motion-x: A large-scale 3d expressive whole-body human motion dataset
Jing Lin, Ailing Zeng, Shunlin Lu, Yuanhao Cai, Ruimao Zhang, Haoqian Wang, and Lei Zhang · 2024
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Humanise: Language-conditioned human motion generation in 3d scenes
Zan Wang, Yixin Chen, Tengyu Liu, Yixin Zhu, Wei Liang, and Siyuan Huang · 2022
Cited alongside, same era.
Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, et al · 2023
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, and Gang Yu · 2023
Cited alongside, same era.
Mofusion: A framework for denoising-diffusion-based motion synthesis
Rishabh Dabral, Muhammad Hamza Mughal, Vladislav Golyanik, and Christian Theobalt · 2023
Cited alongside, same era.
Guided motion diffusion for controllable human motion synthesis
Korrawe Karunratanakul, Konpat Preechakul, Supasorn Suwajanakorn, and Siyu Tang · 2023
Cited alongside, same era.
Perpetual humanoid control for real-time simulated avatars
Zhengyi Luo, Jinkun Cao, Kris Kitani, Weipeng Xu, et al · 2023
Cited alongside, same era.
Closest in time.
Plan, posture and go: Towards open-world text-to-motion generation
Jinpeng Liu, Wenxun Dai, Chunyu Wang, Yiji Cheng, Yansong Tang, and Xin Tong · 2024
Closest in time.
Humantomato: Text-aligned whole-body motion generation
Shunlin Lu, Ling-Hao Chen, Ailing Zeng, Jing Lin, Ruimao Zhang, Lei Zhang, and Heung-Yeung Shum · 2024
Closest in time.
Multi-track timeline control for text-driven 3d human motion generation
Mathis Petrovich, Or Litany, Umar Iqbal, Michael J Black, Gul Varol, Xue Bin Peng, and Davis Rempe · 2024
Closest in time.
Human motion diffusion as a generative prior
Yonatan Shafir, Guy Tevet, Roy Kapon, and Amit H Bermano · 2024
Closest in time.
Autoregressive model beats diffusion: Llama for scalable image generation
Peize Sun, Yi Jiang, Shoufa Chen, Shilong Zhang, Bingyue Peng, Ping Luo, and Zehuan Yuan · 2024
Closest in time.
Scaling laws with vocabulary: Larger models deserve larger vocabularies
Chaofan Tao, Qian Liu, Longxu Dou, Niklas Muennighoff, Zhongwei Wan, Ping Luo, Min Lin, and Ngai Wong · 2024
Closest in time.
Visual autoregressive modeling: Scalable image generation via next-scale prediction
Keyu Tian, Yi Jiang, Zehuan Yuan, Bingyue Peng, and Liwei Wang · 2024
Closest in time.
Tlcontrol: Trajectory and language control for human motion synthesis
Weilin Wan, Zhiyang Dou, Taku Komura, Wenping Wang, Dinesh Jayaraman, and Lingjie Liu · 2024
Closest in time.
Motionllm: Multimodal motion-language learning with large language models
Qi Wu, Yubo Zhao, Yifan Wang, Yu-Wing Tai, and Chi-Keung Tang · 2024
Closest in time.
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 · 2024
Closest in time.
Inter-x: Towards versatile human-human interaction analysis
Liang Xu, Xintao Lv, Yichao Yan, Xin Jin, Shuwen Wu, Congsheng Xu, Yifan Liu, Yizhou Zhou, Fengyun Rao, Xingdong Sheng, et al · 2024
Closest in time.
Animationgpt:an aigc tool for generating game combat motion assets
Liao Yihao, Fu Yiyu, Cheng Ziming, and Wang Jiangfeiyang · 2024
Closest in time.
Smoodi: Stylized motion diffusion model
Lei Zhong, Yiming Xie, Varun Jampani, Deqing Sun, and Huaizu Jiang · 2024
Closest in time.