{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/freemotion-a-unified-framework-for-number","title":"FreeMotion: A Unified Framework for Number-free Text-to-Motion Synthesis","arxiv_id":"2405.15763","date":"2024-05-24","proceeding":null,"authors":["Ke Fan","Junshu Tang","Weijian Cao","Ran Yi","Moran Li","Jingyu Gong","Jiangning Zhang","Yabiao Wang","Chengjie Wang","Lizhuang Ma"],"abstract":"Text-to-motion synthesis is a crucial task in computer vision. Existing methods are limited in their universality, as they are tailored for single-person or two-person scenarios and can not be applied to generate motions for more individuals. To achieve the number-free motion synthesis, this paper reconsiders motion generation and proposes to unify the single and multi-person motion by the conditional motion distribution. Furthermore, a generation module and an interaction module are designed for our FreeMotion framework to decouple the process of conditional motion generation and finally support the number-free motion synthesis. Besides, based on our framework, the current single-person motion spatial control method could be seamlessly integrated, achieving precise control of multi-person motion. Extensive experiments demonstrate the superior performance of our method and our capability to infer single and multi-human motions simultaneously.","url_abs":"https://arxiv.org/abs/2405.15763v1","url_pdf":"https://arxiv.org/pdf/2405.15763v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"motion-generation","task_name":"Motion Generation"},{"task_slug":"motion-synthesis","task_name":"Motion Synthesis"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/motion-synthesis-on-interhuman","task":"Motion Synthesis","dataset":"InterHuman","model":"FreeMotion","rank_in_archive_order":5,"of":10,"metrics":{"FID":"6.740","MMDist":"3.848","MModality":"1.226","R-Precision Top3":"0.544"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/2405.15763","atlas_url":"https://app.syntology.ai/?focus=2405.15763","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}