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The aim is to develop a framework that ensures consistent 3D generation from a single RGB image while addressing geometric and semantic challenges.

UniCross3D: Unified Cross‐View and Cross‐Domain Diffusion for Consistent Single‐Image 3D Generation

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The aim is to develop a framework that ensures consistent 3D generation from a single RGB image while addressing geometric and semantic challenges.
Introduced a diffusion framework called UniCross3D for 3D generation.
Implemented cross-view latent regularization to enhance geometric consistency.
Applied a cross-domain mutual information objective to align synthesized color and normal maps.
Conducted extensive experiments comparing the new approach with state-of-the-art methods.
Achieved significantly improved view consistency compared to existing methods.
Enhanced semantic alignment in generated 3D models.
Produced higher-fidelity reconstructions under challenging textures and ambiguous viewpoints.

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Demonstrates improved 3D generation consistency in single RGB images, suggesting enhanced visual fidelity.

Jun et al. (2026) studied this question.

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