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SweetDreamer: Aligning Geometric Priors in 2D Diffusion for Consistent Text-to-3D
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2026-02-21 18:37:58
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SweetDreamer: Aligning Geometric Priors in 2D Diffusion for Consistent Text-to-3D SweetDreamer: Aligning Geometric Priors in 2D Diffusion for Consistent Text-to-3D ICLR 2024 Weiyu Li 1,2 , Rui Chen 3,4 , Xuelin Chen 4 , Ping Tan 1,2 1 HKUST , 2 Light Illusions , 3 South China University of Technology , 4 Tencent AI Lab Arxiv Paper Code Video Abstract Lifting 2D observations in pre-trained diffusion models to a 3D world for text-to-3D is inherently ambiguous. 2D diffusion models solely learn view-agnostic priors and thus lack 3D knowledge during the lifting, leading to the multi-view inconsistency problem. Our key finding reveals that this problem primarily stems from geometric inconsistency, and addressing ambiguously placed geometries substantially mitigates the issue in the final outcomes. Therefore, we focus on improving t...
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