Please do not hesitate to reach out to the nerfstudio team with any questions via Discord. Have feature requests? Want to add your brand-spankin’-new NeRF model? Have a new dataset? We welcome contributions! So we’re here to help with tutorials, documentation, and more! As researchers, we know just how hard it is to get onboarded with this next-gen technology. We are committed to providing learning resources to help you understand the basics of (if you’re just getting started), and keep up-to-date with (if you’re a seasoned veteran) all things NeRF. It is currently developed by Berkeley students and community contributors. Nerfstudio initially launched as an opensource project by Berkeley students in KAIR lab at Berkeley AI Research (BAIR) in October 2022 as a part of a research project ( paper). This is a contributor-friendly repo with the goal of building a community where users can more easily build upon each other’s contributions. With more modular NeRFs, we hope to create a more user-friendly experience in exploring the technology. The library supports a more interpretable implementation of NeRFs by modularizing each component. Nerfstudio provides a simple API that allows for a simplified end-to-end process of creating, training, and testing NeRFs.
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