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Generalized-Shuffled-Linear-Regression

Code for the ICCV 2021 paper: Generalized Shuffled Linear Regression.

Authors: Feiran Li, Kent Fujiwara, Fumio Okura, and Yasuyuki Matsushita

Teaser

UPDATE: The objective in Eq.7 should be corrected to <img src="http://www.sciweavers.org/tex2img.php?eq=%20%5C%7C%20PAx%20-%20PP%5ETb%20%5C%7C%20%5E2&bc=White&fc=Black&im=jpg&fs=12&ff=arev&edit=0" align="center" border="0" alt=" \| PAx - PP^Tb \| ^2" width="122" height="21" />. The following analysis remain the same.

1. Run the demo

For image registration and point cloud registration:
For isometric shape matching:

2. Related works

Other implementations of shuffled linear regression:
Techniques for speed up:

The main limitation of our current implementation lies in time efficiency, which is dominated by the LAP solver. Some CUDA-based Hungarian algorithms like this and this may help to address this problem.

3. Contact

Please feel free to raise an issue or email to li.feiran@ist.osaka-u.ac.jp if you have any question regarding the paper or any suggestions for further improvements.

4. Citation

If you find this code helpful, thanks for citing our work as

@inproceedings{li2021gslr,
title = {Generalized Shuffled Linear Regression},
author = {Feiran Li and Kent Fujiwara and Fumio Okura and Yasuyuki Matsushita},
booktitle = {IEEE/CVF International Conference on Computer Vision (ICCV)},
year = {2021}
}