Plug-and-play point-cloud rendering
Project description
Pointersect: Neural Rendering with Cloud-Ray Intersection
[Website] [Paper] [Docs] [Examples] [Videos]
Pointersect is a plug-and-play method for rendering point clouds. It is differentiable and does not require per-scene optimization.
Usage
Given a point cloud and a ray, pointersect returns:
- the intersection point between the ray and the underlying surface represented by the point cloud;
- surface normal at the intersection point; and
- color/material interpolation weights of neighboring points.
You can use point clouds containing only xyz---neither color nor vertex normal is needed.
Examples
- We use the surface normal estimated by pointersect to relight a point cloud.
- Even though pointersect is designed to render clean point clouds, here is an example where we use a pretrained pointersect model to render a lidar-scanned point cloud without any optimization.
- Edit and render without re-optimization.
- We use pointersect with path tracing to render the global illumination of a scene.
How to use
You can use pointersect by installing the pypi package:
pip install pointersect
or
# in the repo root
pip install .
We provide API, command line tool, and training script for using pointersect. See the documentation for instructions.
We also provide a few examples if you want to jump in directly :)
Citation
If you use this software package, please cite our paper:
@inproceedings{chang2023pointersect,
author={Jen-Hao Rick Chang and Wei-Yu Chen and Anurag Ranjan and Kwang Moo Yi and Oncel Tuzel},
title={Pointersect: Neural Rendering with Cloud-Ray Intersection},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
year = {2023}
}
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