{"id":21147737,"url":"https://github.com/openmotionlab/motionchain","last_synced_at":"2026-01-03T03:03:20.726Z","repository":{"id":231265548,"uuid":"781306673","full_name":"OpenMotionLab/MotionChain","owner":"OpenMotionLab","description":"MotionChain: Conversational Motion Controllers via Multimodal Prompts","archived":false,"fork":false,"pushed_at":"2024-07-22T12:14:16.000Z","size":86,"stargazers_count":54,"open_issues_count":1,"forks_count":0,"subscribers_count":9,"default_branch":"main","last_synced_at":"2025-01-21T07:43:08.828Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/OpenMotionLab.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-04-03T06:14:03.000Z","updated_at":"2025-01-20T07:12:31.000Z","dependencies_parsed_at":"2024-11-20T09:37:24.202Z","dependency_job_id":"c351c06a-6b9b-48d2-a813-eaa8cb42987c","html_url":"https://github.com/OpenMotionLab/MotionChain","commit_stats":null,"previous_names":["openmotionlab/motionchain"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OpenMotionLab%2FMotionChain","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OpenMotionLab%2FMotionChain/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OpenMotionLab%2FMotionChain/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/OpenMotionLab%2FMotionChain/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/OpenMotionLab","download_url":"https://codeload.github.com/OpenMotionLab/MotionChain/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243589344,"owners_count":20315471,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-20T09:18:15.356Z","updated_at":"2026-01-03T03:03:15.693Z","avatar_url":"https://github.com/OpenMotionLab.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv align= \"center\"\u003e\n    \u003ch1\u003e Official repo for MotionChain\u003c/h1\u003e\n\n\u003c/div\u003e\n\n\u003cdiv align=\"center\"\u003e\n    \u003ch3\u003e MotionChain: Conversational Motion Controllers via Multimodal Prompts\u003c/h3\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003ca href=\"https://arxiv.org/pdf/2404.01700\"\u003eArxiv Paper\u003c/a\u003e •\n  Demo •\n  \u003ca href=\"#️-faq\"\u003eFAQ\u003c/a\u003e •\n  \u003ca href=\"#-citation\"\u003eCitation\u003c/a\u003e\n\u003c/p\u003e\n\n\u003c/div\u003e\n\n\u003cdiv align=\"center\"\u003e\n\u003c/div\u003e\n\n## Intro MotionChain\n\nMotionChain is a unified\nvision-motion-language generative pre-trained model, which performs **conversational**\ngeneration tasks via **multi-modal** inputs with language models.\n\n\u003cdetails open=\"open\"\u003e\n    \u003csummary\u003e\u003cb\u003eTechnical details\u003c/b\u003e\u003c/summary\u003e\n\nRecent advancements in language models have demonstrated their adeptness in conducting multi-turn dialogues and retaining conversational context. However, this proficiency remains largely unexplored in other multimodal generative models, particularly in human motion models. By integrating multi-turn conversations in controlling continuous virtual human movements, generative human motion models can achieve an intuitive and step-by-step process of human task execution for humanoid robotics, game agents, or other embodied systems. In this work, we present MotionChain, a conversational human motion controller to generate continuous and long-term human motion through multimodal prompts. Specifically, MotionChain consists of multi-modal tokenizers that transform various data types such as text, image, and motion, into discrete tokens, coupled with a Vision-Motion-aware Language model. By leveraging large-scale language, vision-language, and vision-motion data to assist motion-related generation tasks, MotionChain thus comprehends each instruction in multi-turn conversation and generates human motions followed by these prompts. Extensive experiments validate the efficacy of MotionChain, demonstrating state-of-the-art performance in conversational motion generation, as well as more intuitive manners of controlling and interacting with virtual humans.\n\n\u003cimg width=\"1194\" alt=\"pipeline\" src=\"./assets/images/pipeline.png\"\u003e\n\u003c/details\u003e\n\n## 🚩 News\n\n- [2024/07/15] [Conversation dataset](https://huggingface.co/datasets/OpenMotionLab/MotionChain_Conv) released. \n- [2024/04/02] Upload paper and init project 🔥🔥🔥\n\n## ⚡ Quick Start\n\n\u003c!-- \u003cdetails\u003e\n  \u003csummary\u003e\u003cb\u003eSetup and download\u003c/b\u003e\u003c/summary\u003e\n\n\u003c/details\u003e --\u003e\n\n## ▶️ Demo\n\n\u003c!-- \u003cdetails\u003e\n  \u003csummary\u003e\u003cb\u003eWebui\u003c/b\u003e\u003c/summary\u003e\n\n\n\u003c/details\u003e --\u003e\n\n## 👀 Visualization\n\n## ⚠️ FAQ\n\n\u003cdetails\u003e \u003csummary\u003e\u003cb\u003eQuestion-and-Answer\u003c/b\u003e\u003c/summary\u003e\n\n\u003c/details\u003e\n\u003c/details\u003e\n\n## 📖 Citation\n\nIf you find our code or paper helps, please consider citing:\n\n```bibtex\n@misc{jiang2024motionchain,\n      title={MotionChain: Conversational Motion Controllers via Multimodal Prompts},\n      author={Biao Jiang and Xin Chen and Chi Zhang and Fukun Yin and Zhuoyuan Li and Gang YU and Jiayuan Fan},\n      year={2024},\n      eprint={2404.01700},\n      archivePrefix={arXiv},\n      primaryClass={cs.CV}\n}\n```\n\n## Acknowledgments\n\nThanks to [BEDLAM](https://github.com/pixelite1201/BEDLAM), [TMR](https://github.com/Mathux/TMR), [vector-quantize-pytorch](https://github.com/lucidrains/vector-quantize-pytorch), [Motion-GPT](https://github.com/OpenMotionLab/MotionGPT), [Motion-latent-diffusion](https://github.com/ChenFengYe/motion-latent-diffusion), [T2m-gpt](https://github.com/Mael-zys/T2M-GPT), [TEMOS](https://github.com/Mathux/TEMOS), [ACTOR](https://github.com/Mathux/ACTOR), [HumanML3D](https://github.com/EricGuo5513/HumanML3D) and [joints2smpl](https://github.com/wangsen1312/joints2smpl), our code is partially borrowing from them.\n\n## License\n\nThis code is distributed under an [MIT LICENSE](LICENSE).\n\nNote that our code depends on other libraries, including SMPL, SMPL-X, PyTorch3D, and uses datasets which each have their own respective licenses that must also be followed.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopenmotionlab%2Fmotionchain","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fopenmotionlab%2Fmotionchain","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fopenmotionlab%2Fmotionchain/lists"}