web_demo.mp4
The program is tested with Python 3.8+ and torch 1.13.1 and dependencies in requirements.txt
.
You will also need to install the following from sources:
The code is still under refactoring so it still contains hardcode and bugs.
- Hloc need to run first in order to obtain the sfm model (in this case we use triangulation from superpoint+superglue).
- Extract a subset of the dataset to train nerf on by
preprocessing.py
. - Generate novel poses using
create_novel_pose.py
- Generate synthetic images by using
view_synthesis.py
- Generate descriptors by matching using
generate_synthetic.py
- Finally training both synthetic and original data using Feat2map
Consider citing if you find this usefull
@article{bui2024leveraging,
title={Leveraging Neural Radiance Field in Descriptor Synthesis for Keypoints Scene Coordinate Regression},
author={Bui, Huy-Hoang and Bui, Bach-Thuan and Tran, Dinh-Tuan and Lee, Joo-Ho},
booktitle={2024 IEEE/RSJ International Conference on Intelligent Robotics and Systems},
year={2024}
}
We thank the author of Hloc, and nerfstudio for providing their opensource contribution.