Nerfstudio: A Modular Framework for Neural Radiance Field Development
원문 초록
Neural Radiance Fields (NeRF) are a rapidly growing area of research with wide-ranging applications in computer vision, graphics, robotics, and more. In order to streamline the development and deployment of NeRF research, we propose a modular PyTorch framework, Nerfstudio. Our framework includes plug-and-play components for implementing NeRF-based methods, which make it easy for researchers and practitioners to incorporate NeRF into their projects. Additionally, the modular design enables support for extensive real-time visualization tools, streamlined pipelines for importing captured in-the-wild data, and tools for exporting to video, point cloud and mesh representations. The modularity of Nerfstudio enables the development of Nerfacto, our method that combines components from recent papers to achieve a balance between speed and quality, while also remaining flexible to future modifications. To promote community-driven development, all associated code and data are made publicly available with open-source licensing at https://nerf.studio.
함께 살펴볼 논문
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UnMix-NeRF: Spectral Unmixing Meets Neural Radiance Fields
Self-Supervised Multimodal NeRF for Autonomous Driving
R3eVision: A Survey on Robust Rendering, Restoration, and Enhancement for 3D Low-Level Vision
Speedy Deformable 3D Gaussian Splatting: Fast Rendering and Compression of Dynamic Scenes
Depth-Guided Bundle Sampling for Efficient Generalizable Neural Radiance Field Reconstruction
GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis
토론
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