Magic-Boost: Boost 3D Generation with Multi-View Conditioned Diffusion

Understand

Benefiting from the rapid development of 2D diffusion models, 3D content generation has witnessed significant progress.

• One promising solution is to finetune the pre-trained 2D diffusion models to produce multi-view images and then reconstruct them into 3D assets via feed-forward sparse-view reconstruction models.
• However, limited by the 3D inconsistency in the generated multi-view images and the low reconstruction resolution of the feed-forward reconstruction models, the generated 3d assets are still limited to incorrect geometries and blurry textures.
• To address this problem, we present a multi-view based refine method, named Magic-Boost, to further refine the generation results.