ICLR2025
A3D: Does Diffusion Dream about 3D Alignment?
Savva Victorovich Ignatyev, Nina Konovalova, Daniil Selikhanovych, Oleg Voynov, Nikolay Patakin, Ilya Olkov, Dmitry Senushkin, Alexey Artemov, Anton Konushin, Alexander Filippov, Peter Wonka, Evgeny Burnaev
摘要
Figure 1 : Our method A3D enables conditioning text-to-3D generation process on a set of text prompts to jointly generate a set of 3D objects with a shared structure (top). This enables a user to make "hybrids" combined of different parts from multiple aligned objects (middle), or perform text-driven structure-preserving transformation of an input 3D model (bottom).