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FlashTex: Fast Relightable Mesh Texturing with LightControlNet

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arxiv 2402.13251 v3 pith:KVYEJQAT submitted 2024-02-20 cs.GR cs.CVcs.LG

Kangle Deng , Timothy Omernick , Alexander Weiss , Deva Ramanan , Jun-Yan Zhu , Tinghui Zhou , Maneesh Agrawala This is my paper · ORCID
classification cs.GRcs.CVcs.LG
keywords lightcontrolnetlightingmeshtextureapproachfastmaterialmodel
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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.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. MeshGen: Generating PBR Textured Mesh with Render-Enhanced Auto-Encoder and Generative Data Augmentation

    cs.GR 2025-05 conditional novelty 6.0 of 10

    A single photo is converted into a 3D mesh with PBR textures using a render-enhanced auto-encoder, two data-augmentation schemes, and a multi-view texturing pipeline, with the claimed result being the best quality amo...

  2. MatCLIP: Light- and Shape-Insensitive Assignment of PBR Material Models

    cs.CV 2025-01 conditional novelty 6.0 of 10

    MatCLIP learns a shape- and lighting-robust CLIP-based descriptor of PBR materials from 42 renderings per material and uses it to match materials to image regions, reaching 76.69% top-1 accuracy.

  3. MV-Adapter: Multi-view Consistent Image Generation Made Easy

    cs.CV 2024-12 conditional novelty 5.0 of 10

    An adapter bolts multi-view generation onto frozen text-to-image diffusion models, producing consistent views at up to 768 resolution on SDXL.

  4. DoubleDiffusion: Combining Heat Diffusion with Denoising Diffusion for Texture Generation on 3D Meshes

    cs.CV 2025-01 conditional novelty 4.0 of 10

    DoubleDiffusion combines DiffusionNet's heat-diffusion feature propagation with a standard denoising diffusion loop to generate per-vertex RGB textures directly on 3D meshes.

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