FocalDreamer: Text-driven 3D Editing via Focal-fusion Assembly

Autor:	Li, Yuhan, Dou, Yishun, Shi, Yue, Lei, Yu, Chen, Xuanhong, Zhang, Yi, Zhou, Peng, Ni, Bingbing
Rok vydání:	2023
Předmět:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Graphics Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	While text-3D editing has made significant strides in leveraging score distillation sampling, emerging approaches still fall short in delivering separable, precise and consistent outcomes that are vital to content creation. In response, we introduce FocalDreamer, a framework that merges base shape with editable parts according to text prompts for fine-grained editing within desired regions. Specifically, equipped with geometry union and dual-path rendering, FocalDreamer assembles independent 3D parts into a complete object, tailored for convenient instance reuse and part-wise control. We propose geometric focal loss and style consistency regularization, which encourage focal fusion and congruent overall appearance. Furthermore, FocalDreamer generates high-fidelity geometry and PBR textures which are compatible with widely-used graphics engines. Extensive experiments have highlighted the superior editing capabilities of FocalDreamer in both quantitative and qualitative evaluations. Comment: Project website: https://focaldreamer.github.io
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2308.10608 Zobrazit plný text záznamu View this record from Arxiv