Journal ArticleUnknown
Structured 3D Latents for Scalable and Versatile 3D Generation
Authors
Author Affiliations
Tsinghua University, University of Science and Technology Chittagong, Microsoft Research (United Kingdom)
Year2025
Citations114
Abstract
We introduce a novel 3D generation method for versatile and high-quality 3D asset creation. The cornerstone is a unified Structured LATent (SLat) representation which allows decoding to different output formats, such as Radiance Fields, 3D Gaussians, and meshes. This is achieved by integrating a sparsely-populated 3D grid with dense multiview visual features extracted from a powerful vision foundation model, comprehensively capturing both structural (geometry) and textural (appearance) information while maintaining flexibility during decoding.We employ rectified flow transformers tailored for SLat as our 3D generation models and train models with up to 2 billion parameters on a large 3D asset dataset of 500K diverse objects. Our model generates high-quality results with text or image conditions, significantly surpassing existing methods, including recent…
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