Lakonik/SSDNeRF
PyTorch implementation of a single-stage diffusion model for Neural Radiance Fields (NeRF) used for unified 3D generation and reconstruction.
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SSDNeRF implements a single-stage diffusion-based approach to Neural Radiance Fields for simultaneously handling 3D scene generation and reconstruction. The method leverages diffusion models to enable single-view 3D reconstruction and unconditional 3D generation. The codebase reproduces all experiments from the paper including results on the KITTI Cars dataset and provides a GUI demo for visualization.
Frequently asked
- What is Lakonik/SSDNeRF?
- PyTorch implementation of a single-stage diffusion model for Neural Radiance Fields (NeRF) used for unified 3D generation and reconstruction.
- Is SSDNeRF open source?
- Yes — Lakonik/SSDNeRF is open source, released under the MIT license.
- What language is SSDNeRF written in?
- Lakonik/SSDNeRF is primarily written in Python.
- How popular is SSDNeRF?
- Lakonik/SSDNeRF has 447 stars on GitHub.
- Where can I find SSDNeRF?
- Lakonik/SSDNeRF is on GitHub at https://github.com/Lakonik/SSDNeRF.