{"ID":2856491,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.11650","arxiv_id":"2510.11650","title":"InfiniHuman: Infinite 3D Human Creation with Precise Control","abstract":"Generating realistic and controllable 3D human avatars is a long-standing challenge, particularly when covering broad attribute ranges such as ethnicity, age, clothing styles, and detailed body shapes. Capturing and annotating large-scale human datasets for training generative models is prohibitively expensive and limited in scale and diversity. The central question we address in this paper is: Can existing foundation models be distilled to generate theoretically unbounded, richly annotated 3D human data? We introduce InfiniHuman, a framework that synergistically distills these models to produce richly annotated human data at minimal cost and with theoretically unlimited scalability. We propose InfiniHumanData, a fully automatic pipeline that leverages vision-language and image generation models to create a large-scale multi-modal dataset. User study shows our automatically generated identities are undistinguishable from scan renderings. InfiniHumanData contains 111K identities spanning unprecedented diversity. Each identity is annotated with multi-granularity text descriptions, multi-view RGB images, detailed clothing images, and SMPL body-shape parameters. Building on this dataset, we propose InfiniHumanGen, a diffusion-based generative pipeline conditioned on text, body shape, and clothing assets. InfiniHumanGen enables fast, realistic, and precisely controllable avatar generation. Extensive experiments demonstrate significant improvements over state-of-the-art methods in visual quality, generation speed, and controllability. Our approach enables high-quality avatar generation with fine-grained control at effectively unbounded scale through a practical and affordable solution. We will publicly release the automatic data generation pipeline, the comprehensive InfiniHumanData dataset, and the InfiniHumanGen models at https://yuxuan-xue.com/infini-human.","short_abstract":"Generating realistic and controllable 3D human avatars is a long-standing challenge, particularly when covering broad attribute ranges such as ethnicity, age, clothing styles, and detailed body shapes. Capturing and annotating large-scale human datasets for training generative models is prohibitively expensive and limi...","url_abs":"https://arxiv.org/abs/2510.11650","url_pdf":"https://arxiv.org/pdf/2510.11650v1","authors":"[\"Yuxuan Xue\",\"Xianghui Xie\",\"Margaret Kostyrko\",\"Gerard Pons-Moll\"]","published":"2025-10-13T17:29:55Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[\"Diffusion Model\"]","project_urls":"[\"https://yuxuan-xue.com/infini-human\"]","has_code":false,"code_links":[{"ID":608354,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2856491,"paper_url":"https://arxiv.org/abs/2510.11650","paper_title":"InfiniHuman: Infinite 3D Human Creation with Precise Control","repo_url":"https://github.com/YuxuanSnow/InfiniHuman","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0},{"ID":608355,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2856491,"paper_url":"https://arxiv.org/abs/2510.11650","paper_title":"InfiniHuman: Infinite 3D Human Creation with Precise Control","repo_url":"https://github.com/yuxuansnow/InfiniHuman","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0},{"ID":608356,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2856491,"paper_url":"https://arxiv.org/abs/2510.11650","paper_title":"InfiniHuman: Infinite 3D Human Creation with Precise Control","repo_url":"https://github.com/nerfies/nerfies.github.io","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}