Boosting3D: High-Fidelity Image-to-3D by Boosting 2D Diffusion Prior to 3D Prior with Progressive Learning

Understand

We present Boosting3D, a multi-stage single image-to-3D generation method that can robustly generate reasonable 3D objects in different data domains.

• The point of this work is to solve the view consistency problem in single image-guided 3D generation by modeling a reasonable geometric structure.
• For this purpose, we propose to utilize better 3D prior to training the NeRF.
• More specifically, we train an object-level LoRA for the target object using original image and the rendering output of NeRF.