InfiniHuman: Realistic 3D Human Creation with Precise Control

Generating realistic and controllable 3D human avatars is a long-standing challenge. The difficulty increases when covering a broad range of attributes 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 both scale and diversity. The central question we address in this paper is: Can we distill existing foundation models to generate theoretically unbounded richly annotated 3D human data? We introduce InfiniHuman, a novel framework to distill these models synergistically, to generate richly annotated human data with minimal cost and theoretically unlimited scalability. Specifically, we propose InfiniHumanData, a fully automatic pipeline that leverages vision-language and image generation models to create a large-scale multi-modal dataset. Remarkably, users cannot distinguish our automatically generated identities from scan renderings. InfiniHumanData contains 111K identities and covers unprecedented diversity in ethnicity, age, clothing styles, and more. Each identity is annotated with multi-granularity text descriptions, multi-view RGB images, detailed clothing images, and SMPL body shape parameters. Based on this, we learn 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 that InfiniHuman significantly surpasses existing state-of-the-art methods in terms of visual quality, generation speed, and controllability. Importantly, our approach democratizes high-quality avatar generation with fine-grained control at infinite scale through a practical and affordable solution. To facilitate future research, we will publicly release our automatic data generation pipeline and the comprehensive dataset InfiniHumanData, and the generative models InfiniHumanGen. The code and data of InfiniHuman is publicly available at https://yuxuan-xue.com/infini-human.