FocalDreamer: Text-Driven 3D Editing via Focal-Fusion Assembly
Yuhan Li, Yishun Dou, Yue Shi, Yu Lei, Xuanhong Chen, Yi Zhang, Peng Zhou, Bingbing Ni
摘要
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.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了最后一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper37
- DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content CreationJiaxiang Tang, Jiawei Ren, Hang Zhou, Ziwei Liu 等ICLR 2024 · 被引用 955 次
- Progressive3D: Progressively Local Editing for Text-to-3D Content Creation with Complex Semantic PromptsXinhua Cheng, Tianyu Yang, Jianan Wang, Yu Li 等ICLR 2024 · 被引用 58 次
- MVInpainter: Learning Multi-View Consistent Inpainting to Bridge 2D and 3D EditingChenjie Cao, Chaohui Yu, Fan Wang, Xiangyang Xue 等NeurIPS 2024 · 被引用 36 次
- Nano3D: A Training-Free Approach for Efficient 3D Editing Without MasksJunliang Ye, Shenghao Xie, Ruowen Zhao, Zhengyi Wang 等ICLR 2026 · 被引用 32 次
- SketchDream: Sketch-based Text-To-3D Generation and EditingFeng-Lin Liu, Hongbo Fu, Yu-Kun Lai, Lin GaoSIGGRAPH 2024 · 被引用 30 次
它引用的顶会 Paper23
- Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh 等ICML 2021 · 被引用 47,906 次
- Denoising Diffusion Probabilistic ModelsJonathan Ho, Ajay Jain, Pieter AbbeelNeurIPS 2020 · 被引用 35,902 次
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser 等CVPR 2022 · 被引用 13,123 次
- Adding Conditional Control to Text-to-Image Diffusion ModelsLvmin Zhang, Anyi Rao, Maneesh AgrawalaICCV 2023 · 被引用 6,759 次
- Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content CreationRui Chen, Yongwei Chen, Ningxin Jiao, Kui JiaICCV 2023 · 被引用 769 次
相关 Paper
- A3D: Does Diffusion Dream about 3D Alignment?Savva Victorovich Ignatyev, Nina Konovalova, Daniil Selikhanovych, Oleg Voynov 等ICLR 2025
- HandDreamer: Zero-Shot Text to 3D Hand Model Generation using Corrective Hand Shape GuidanceGreen Rosh, Prateek Kukreja, Vishakha SR, Pawan Prasad B HCVPR 2026
- TextureDreamer: Image-Guided Texture Synthesis through Geometry-Aware DiffusionYu-Ying Yeh, Jia-Bin Huang, Changil Kim, Lei Xiao 等CVPR 2024 · 被引用 31 次
- CustomTex: High-fidelity Indoor Scene Texturing via Multi-Reference CustomizationWeilin Chen, Jiahao Rao, Wenhao Wang, Xinyang Li 等CVPR 2026 · 被引用 1 次
- Rethinking Score Distilling Sampling for 3D Editing and GenerationXingyu Miao, Haoran Duan, Yang Long, Jungong HanICML 2025
