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.
BathyFacto: Refraction-Aware Two-Media Neural Radiance Fields for Bathymetry
Department of Geodesy and Geoinformation, TU Wien（维也纳技术大学测绘与地理信息系）；Institute of Photogrammetry and Remote Sensing (IPF), Karlsruhe Institute of Technology (KIT)（卡尔斯鲁厄理工学院测绘与遥感研究所）；Unit of Geometry and Surveying, University of Innsbruck（因斯布鲁克大学几何与测绘单位）
Leveraging Neural Radiance Field in Descriptor Synthesis for Keypoints Scene Coordinate Regression
Graduate School of Information Science and Engineering, Ritsumeikan University（立命馆大学信息科学与工程研究生院）；College of Information Science, Ritsumeikan University（立命馆大学信息科学学院）
Advancing Talking Head Generation: A Comprehensive Survey of Multi-Modal Methodologies, Datasets, Evaluation Metrics, and Loss Functions
Engineering Sciences, Homi Bhabha National Institute Training School Complex（工程科学，霍米·巴赫瓦全国研究所培训学校）；Computer and Informatics Group, VECC 1/AF（计算机与信息组，VECC 1/AF）
MARS: An Instance-aware, Modular and Realistic Simulator for Autonomous Driving
AIR, Tsinghua University（清华大学AIR）；System Thurst, HKUST(GZ)（香港科技大学（广州）System Thurst）；HKUST（香港科技大学）；McGill University（麦吉尔大学）；Beijing Institute of Technology（北京理工大学）；National University of Singapore（新加坡国立大学）；HKU（香港大学）；University of Wisconsin Madison（威斯康星大学麦迪逊分校）；Xi’an University of Architecture and Technology（西安建筑科技大学）；Imperial College London（伦敦帝国学院）；Zhejiang University（浙江大学）
