Customize your NeRF: Adaptive Source Driven 3D Scene Editing via Local-Global Iterative Training
Runze He, Shaofei Huang, Xuecheng Nie, Tianrui Hui, Luoqi Liu, Jiao Dai, Jizhong Han, Guanbin Li, Si Liu
2024Year
10Top-tier citations
Abstract
Text-Driven Editing Image-Driven Editing Original Scenes (a) (b) (c) "a helmet on the fur" "a V* dog standing in the forest" "a V* shoe on the mat" "a V* hat on the fur" "a V* statue in the exhibition hall" "a Luffy in the exhibition hall" 20 3 daw ei2 个再 优化 一下 blue: textual prompt green: hybrid prompt * Equal contribution (
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Cited by top-tier papers10
- TIP-Editor: An Accurate 3D Editor Following Both Text-Prompts And Image-PromptsJingyu Zhuang, Di Kang, Yan-Pei Cao, Guanbin Li et al.SIGGRAPH 2024 · 59 citations
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- CTRL-D: Controllable Dynamic 3D Scene Editing with Personalized 2D DiffusionKai He, Chin-Hsuan Wu, Igor GilitschenskiCVPR 2025
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- Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh et al.ICML 2021 · 47,906 citations
- Denoising Diffusion Probabilistic ModelsJonathan Ho, Ajay Jain, Pieter AbbeelNeurIPS 2020 · 35,902 citations
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser et al.CVPR 2022 · 13,123 citations
- Photorealistic Text-to-Image Diffusion Models with Deep Language UnderstandingChitwan Saharia, William Chan, Saurabh Saxena, Lala Li et al.NeurIPS 2022 · 8,965 citations
- Zero-Shot Text-to-Image GenerationAditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray et al.ICML 2021 · 6,356 citations
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