GLOSS: Geometric Local Self-Similarity Learning for Faithful Reference-Guided Texture Fill
cs.GR, cs.CV, cs.LG
Submitted: 2026-08-26
Updated: 2026-08-26
Comments: 22 pages, 17 figures, project page https://chenyuecai.github.io/gloss-page/
Code: https://github.com/Comfy-Org/ComfyUI
Project page: https://chenyuecai.github.io/gloss-page
License: http://creativecommons.org/licenses/by/4.0/
The gist: Using conditional image generators, texture artists can explore many single-view looks for an existing 3D shape.
Terminology
Abstract
Using conditional image generators, texture artists can explore many single-view looks for an existing 3D shape. Despite impressive progress, state-of-the-art generative methods still struggle to generate a full object texture while closely adhering to fine scale geometric detail and single view references, leaving little room for artists guidance. Furthermore, current automatic models lack the flexibility for artist to explore multiple textures from varied sources in an interactive and controllable manner. Unlike methods trained on large 3D datasets that generate full object textures from global guidance, our work explores a local and less data-hungry approach to texture with explicit artist control. We leverage the geometric self-similarity and geometry-texture correlation existing in many natural and man-made shapes; and train a shape-specific local texture generation and completion model. This model learns from existing image model priors and a single 3D shape, and is guided by attending to a set of geometry-aware reference patches. The trained shape-specific network can transfer any novel reference to the full target object texture through patchwise inpainting. We show improved or comparable quality to strong image-conditioned texture generation baselines, suggesting local texturing as a promising research direction. Our model also enables local geometry-conditioned texture inpainting, guided by artist-selected references, and generalizes to PBR materials and unseen meshes for texture transfer. We piloted our novel texture fill capability as a Blender addon with several 3D texturing professionals who reported positive feedback on the model's controllability, practical usefulness, and creative affordances.
Sources
- Meta 3D TextureGen: Fast and Consistent Texture Generation for 3D Objects
- Self-Supervised Implicit Attention Priors for Point Cloud Reconstruction
- MaterialMVP: Illumination-Invariant Material Generation via Multi-view PBR Diffusion
- Hunyuan3D 2.1: From Images to High-Fidelity 3D Assets with Production-Ready PBR Material
- Hierarchical Text-Conditional Image Generation with CLIP Latents
- Progressive Distillation for Fast Sampling of Diffusion Models
- Resolution-robust Large Mask Inpainting with Fourier Convolutions
- Native and Compact Structured Latents for 3D Generation
- FlexPainter: Flexible and Multi-View Consistent Texture Generation
- IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models
- SeqTex: Generate Mesh Textures in Video Sequence
- Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation
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