Xharlie/pointnerf
Point-NeRF is a neural radiance field method that uses 3D point clouds with neural features for efficient scene reconstruction and rendering.
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Point-NeRF models radiance fields using neural 3D point clouds with associated features, enabling efficient rendering via ray marching. It can be initialized via deep network inference and finetuned to surpass standard NeRF quality with 30x faster training. The method includes a pruning and growing mechanism to handle errors from external 3D reconstruction methods.
Frequently asked
- What is Xharlie/pointnerf?
- Point-NeRF is a neural radiance field method that uses 3D point clouds with neural features for efficient scene reconstruction and rendering.
- Is pointnerf open source?
- Yes — Xharlie/pointnerf is an open-source project tracked on heatdrop.
- What language is pointnerf written in?
- Xharlie/pointnerf is primarily written in Python.
- How popular is pointnerf?
- Xharlie/pointnerf has 1.2k stars on GitHub.
- Where can I find pointnerf?
- Xharlie/pointnerf is on GitHub at https://github.com/Xharlie/pointnerf.