NaTex: Seamless Texture Generation as Latent Color Diffusion
We present NaTex, a native texture generation framework that predicts texture color directly in 3D space. In contrast to previous approaches that rely on baking 2D multi-view images synthesized by geometry-conditioned Multi-View Diffusion models (MVDs), NaTex avoids several inherent limitations of the MVD pipeline. These include difficulties in handling occluded regions that require inpainting, achieving precise mesh-texture alignment along boundaries, and maintaining cross-view consistency and coherence in both content and color intensity. NaTex features a novel paradigm that addresses the aforementioned issues by viewing texture as a dense color point cloud. Driven by this idea, we propose latent color diffusion, which comprises a geometry-awared color point cloud VAE and a multi-control diffusion transformer (DiT), entirely trained from scratch using 3D data, for texture reconstruction and generation. To enable precise alignment, we introduce native geometry control that conditions the DiT on direct 3D spatial information via positional embeddings and geometry latents. We co-design the VAE-DiT architecture, where the geometry latents are extracted via a dedicated geometry branch tightly coupled with the color VAE, providing fine-grained surface guidance that maintains strong correspondence with the texture. With these designs, NaTex demonstrates strong performance, significantly outperforming previous methods in texture coherence and alignment. Moreover, NaTex also exhibits strong generalization capabilities, either training-free or with simple tuning, for various downstream applications, e.g., material generation, texture refinement, and part segmentation and texturing.
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Zeqiang Lai
admin_assigned
2025-11-21T10:52:23.638Z
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Zeqiang Lai
ZeqiangLai
user
ZeqiangLai
691fda75cce0eb9b6387afc1
Yunfei Zhao
691fda75cce0eb9b6387afc2
Zibo Zhao
admin_assigned
2025-11-21T10:52:58.130Z
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zibo.zhao
cocacola
user
cocacola
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Xin Yang
691fda75cce0eb9b6387afc4
Xin Huang
691fda75cce0eb9b6387afc5
Jingwei Huang
691fda75cce0eb9b6387afc6
Xiangyu Yue
admin_assigned
2025-11-21T10:52:43.076Z
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Xiangyu Yue
xyyue
user
xyyue
691fda75cce0eb9b6387afc7
Chunchao Guo
NaTex: Seamless Texture Generation as Latent Color Diffusion
We present NaTex, a native texture generation framework that predicts texture color directly in 3D space. In contrast to previous approaches that rely on baking 2D multi-view images synthesized by geometry-conditioned Multi-View Diffusion models (MVDs), NaTex avoids several inherent limitations of the MVD pipeline. These include difficulties in handling occluded regions that require inpainting, achieving precise mesh-texture alignment along boundaries, and maintaining cross-view consistency and coherence in both content and color intensity. NaTex features a novel paradigm that addresses the aforementioned issues by viewing texture as a dense color point cloud. Driven by this idea, we propose latent color diffusion, which comprises a geometry-awared color point cloud VAE and a multi-control diffusion transformer (DiT), entirely trained from scratch using 3D data, for texture reconstruction and generation. To enable precise alignment, we introduce native geometry control that conditions the DiT on direct 3D spatial information via positional embeddings and geometry latents. We co-design the VAE-DiT architecture, where the geometry latents are extracted via a dedicated geometry branch tightly coupled with the color VAE, providing fine-grained surface guidance that maintains strong correspondence with the texture. With these designs, NaTex demonstrates strong performance, significantly outperforming previous methods in texture coherence and alignment. Moreover, NaTex also exhibits strong generalization capabilities, either training-free or with simple tuning, for various downstream applications, e.g., material generation, texture refinement, and part segmentation and texturing.
NaTex generates 3D textures directly using latent color diffusion and geometry-aware models, outperforming previous methods in coherence and alignment.
native texture generation 3D space Multi-View Diffusion models latent color diffusion geometry-awared color point cloud VAE multi-control diffusion transformer positional embeddings geometry latents texture coherence alignment material generation texture refinement part segmentation and texturing