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.
翻译:神经辐射场(Neoral Radiance Fields)是一个迅速增长的研究领域,在计算机视觉、图形、机器人等方面应用广泛。为了简化NeRF研究的开发和部署,我们提议了一个模块式PyTorrch框架,Nerfstudio。我们的框架包括用于实施NeRF方法的插座和剧本部分,使研究人员和从业人员很容易将NeRF纳入其项目。此外,模块设计能够支持广泛的实时可视化工具、简化输入在网上收集的数据的管道和向视频、点云和网格图示输出的工具。Nerfstudio的模块化使得Nerfacto得以发展,这是我们将最新论文的组件结合起来,以便在速度和质量之间实现平衡,同时保持对未来修改的灵活性。为了促进社区驱动的发展,所有相关的代码和数据都公开提供,并在https://nerf.studio上提供开放源许可证。