This repository holds all the code and data for the paper:
Self-supervised Correspondence Estimation via Multiview Registration
Mohamed El Banani, Ignacio Rocco, David Novotny, Andrea Vedaldi,
Natalia Neverova, Justin Johnson, Benjamin Graham
If you find this code useful, please consider citing:
@inProceedings{elbanani2023syncmatch,
title={{Self-supervised Correspondence Estimation via Multiview Registration}},
author={El Banani, Mohamed and Rocco, Ignacio and Novotny, David and Vedaldi, Andrea and Neverova, Natalia and Johnson, Justin and Graham, Benjamin}
booktitle={WACV},
year={2023},
}
If you have any questions, please feel free to email me at [email protected].
- How to setup your environment?
- How to download and setup the datasets?
- How to train model and ablations in paper?
- How to run the evaluation?
See the CONTRIBUTING file for how to help out.
SyncMatch is CC-BY-NC licensed, as found in the LICENSE file.
We would like to thank Karan Desai, Richard Higgins, David Fouhey, Daniel Geng, and Dandan Shan for feedback on early drafts of this work.