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FlashTex: Fast Relightable Mesh Texturing with LightControlNet

Authors :
Deng, Kangle
Omernick, Timothy
Weiss, Alexander
Ramanan, Deva
Zhu, Jun-Yan
Zhou, Tinghui
Agrawala, Maneesh
Publication Year :
2024

Abstract

Manually creating textures for 3D meshes is time-consuming, even for expert visual content creators. We propose a fast approach for automatically texturing an input 3D mesh based on a user-provided text prompt. Importantly, our approach disentangles lighting from surface material/reflectance in the resulting texture so that the mesh can be properly relit and rendered in any lighting environment. We introduce LightControlNet, a new text-to-image model based on the ControlNet architecture, which allows the specification of the desired lighting as a conditioning image to the model. Our text-to-texture pipeline then constructs the texture in two stages. The first stage produces a sparse set of visually consistent reference views of the mesh using LightControlNet. The second stage applies a texture optimization based on Score Distillation Sampling (SDS) that works with LightControlNet to increase the texture quality while disentangling surface material from lighting. Our algorithm is significantly faster than previous text-to-texture methods, while producing high-quality and relightable textures.<br />Comment: Project page: https://flashtex.github.io/

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2402.13251
Document Type :
Working Paper