ProEdit: Simple Progression is All You Need for High-Quality 3D Scene Editing

Light field rendering

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NeRF: Representing scenes as neural radiance fields for view synthesis

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Neural sparse voxel fields

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PlenOctrees for real-time rendering of neural radiance fields

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Editing conditional radiance fields

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Learning object-compositional neural radiance field for editable scene rendering

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Learning transferable visual models from natural language supervision

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High-resolution image synthesis with latent diffusion models

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SDEdit: Guided image synthesis and editing with stochastic differential equations

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DIVeR: Real-time and accurate neural radiance fields with deterministic integration for volume rendering

Liwen Wu, Jae Yong Lee, Anand Bhattad, Yu-Xiong Wang, and David Forsyth · 2022

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Plenoxels: Radiance fields without neural networks

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NeRFReN: Neural radiance fields with reflections

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Decomposing NeRF for editing via feature field distillation

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NeuPhysics: Editable neural geometry and physics from monocular videos

Instruct 3D-to-3D: Text instruction guided 3D-to-3D conversion

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Hiromichi Kamata, Yuiko Sakuma, Akio Hayakawa, Masato Ishii, and Takuya Narihira · 2023

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Edit-DiffNeRF: Editing 3D neural radiance fields using 2D diffusion model

Original

Lu Yu, Wei Xiang, and Kang Han · 2023

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ViCA-NeRF: View-consistency-aware 3D editing of neural radiance fields

Jiahua Dong and Yu-Xiong Wang · 2023

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DreamFusion: Text-to-3D using 2D diffusion

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Nerfstudio: A modular framework for neural radiance field development

Matthew Tancik, Ethan Weber, Evonne Ng, Ruilong Li, Brent Yi, Justin Kerr, Terrance Wang, Alexander Kristoffersen, Jake Austin, Kamyar Salahi, Abhik Ahuja, David McAllister, and Angjoo Kanazawa · 2023

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