LATTE3D: Large-scale Amortized Text-To-Enhanced3D Synthesis

arXiv:2403.15385v1 Announce Type: cross
Abstract: Recent text-to-3D generation approaches produce impressive 3D results but require time-consuming optimization that can take up to an hour per prompt. Amortized methods like ATT3D optimize multiple prompts simultaneously to improve efficiency, enabling fast text-to-3D synthesis. However, they cannot capture high-frequency geometry and texture details and struggle to scale to large prompt sets, so they generalize poorly. We introduce LATTE3D, addressing these limitations to achieve fast, high-quality generation on a significantly larger prompt set. Key …

abstract arxiv cs.ai cs.cv cs.gr cs.lg efficiency enabling geometry hour however multiple optimization per prompt prompts results scale struggle synthesis text texture type