Exploration and Improvement of Nerf-based 3D Scene Editing Techniques
Not on the map. Why?
Abstract (arXiv)
NeRF's high-quality scene synthesis capability was quickly accepted by scholars in the years after it was proposed, and significant progress has been made in 3D scene representation and synthesis. However, the high computational cost limits intuitive and efficient editing of scenes, making NeRF's development in the scene editing field facing many challenges. This paper reviews the preliminary explorations of scholars on NeRF in the scene or object editing field in recent years, mainly changing the shape and texture of scenes or objects in new synthesized scenes; through the combination of residual models such as GaN and Transformer with NeRF, the generalization ability of NeRF scene editing has been further expanded, including realizing real-time new perspective editing feedback, multimodal editing of text synthesized 3D scenes, 4D synthesis performance, and in-depth exploration in light and shadow editing, initially achieving optimization of indirect touch editing and detail representation in complex scenes. Currently, most NeRF editing methods focus on the touch points and materials of indirect points, but when dealing with more complex or larger 3D scenes, it is difficult to balance accuracy, breadth, efficiency, and quality. Overcoming these challenges may become the direction of future NeRF 3D scene editing technology.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 12 of its 18 references that are in the map. First posted on arXiv 23 Jan 2024.
Builds on
12 of 18 references.
References · 12
- 2020pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesiscited by 708
- 2023Instruct-NeRF2NeRF: Editing 3D Scenes with Instructionscited by 484
- 2021PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relightingcited by 335
- 2021Editing Conditional Radiance Fieldscited by 222
- 2022NeRF-Editing: Geometry Editing of Neural Radiance Fieldscited by 217
- 2022Modeling Indirect Illumination for Inverse Renderingcited by 168
- 2023TensoIR: Tensorial Inverse Renderingcited by 168
- 2022NeuMesh: Learning Disentangled Neural Mesh-based Implicit Field for Geometry and Texture Editingcited by 142
- 2022Next3D: Generative Neural Texture Rasterization for 3D-Aware Head Avatarscited by 124
- 2023Instruct 3D-to-3D: Text Instruction Guided 3D-to-3D conversioncited by 48
- 2022AniFaceGAN: Animatable 3D-Aware Face Image Generation for Video Avatarscited by 46
- 2023NeMF: Inverse Volume Rendering with Neural Microflake Fieldcited by 34
Built on by
Not cited yet.