ayaanzhaque/instruct-nerf2nerf
A neural radiance field editing system that uses diffusion models to modify 3D scenes based on text instructions.
Not currently ranked — collecting fresh signals.
star history
Instruct-NeRF2NeRF is an ICCV 2023 paper implementation that iteratively updates 3D scene representations using text-guided diffusion models. Built on Nerfstudio and PyTorch, it allows users to edit trained NeRF scenes with natural language commands by projecting image-level edits from a conditioned diffusion model back into the 3D volume.
Frequently asked
- What is ayaanzhaque/instruct-nerf2nerf?
- A neural radiance field editing system that uses diffusion models to modify 3D scenes based on text instructions.
- Is instruct-nerf2nerf open source?
- Yes — ayaanzhaque/instruct-nerf2nerf is open source, released under the MIT license.
- What language is instruct-nerf2nerf written in?
- ayaanzhaque/instruct-nerf2nerf is primarily written in Python.
- How popular is instruct-nerf2nerf?
- ayaanzhaque/instruct-nerf2nerf has 853 stars on GitHub.
- Where can I find instruct-nerf2nerf?
- ayaanzhaque/instruct-nerf2nerf is on GitHub at https://github.com/ayaanzhaque/instruct-nerf2nerf.