Code released as part of the published paper:

Barbed, O. L., Chadebecq, F., Morlana, J., Montiel, J. M., & Murillo, A. C. (2022, December). SuperPoint features in endoscopy. In Imaging Systems for GI Endoscopy, and Graphs in Biomedical Image Analysis: First MICCAI Workshop, ISGIE 2022, and Fourth MICCAI Workshop, GRAIL 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings (pp. 45-55). Springer link ArXiV link

This repository is a modified implementation of:

DeTone, Daniel, Tomasz Malisiewicz, and Andrew Rabinovich. "Superpoint: Self-supervised interest point detection and description." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops. 2018. CVF Open Access Link.

It is based on another implementation by You-Yi Jau and Rui Zhu: https://github.com/eric-yyjau/pytorch-superpoint

The code has been developed as part of the european project EndoMapper.

Consecutive frames	Frames 1 second apart

SIFT	ORB	SuperPoint

E-SuperPoint	E-SuperPoint+S

Developed by Óscar León Barbed, Ana C. Murillo & François Chadebecq, Javier Morlana, José María Martínez Montiel.