https://github.com/macillas/s2dnet
Reproduce S2DNet from Minimal code to load S2DNet weights (ECCV 2020)
Science Score: 10.0%
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Reproduce S2DNet from Minimal code to load S2DNet weights (ECCV 2020)
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Fork of germain-hug/S2DNet-Minimal
Created over 3 years ago
· Last pushed about 4 years ago
https://github.com/MACILLAS/S2DNet/blob/main/
## S2DNet Minimal Loading Code (ECCV 2020)
Minimal code to load S2DNet weights, from the paper [S2DNet : Learning Image Features for Accurate Sparse-to-Dense Matching
](https://arxiv.org/abs/2004.01673)
You can download the pre-trained weights [here](https://www.dropbox.com/s/hnv51iwu4hn82rj/s2dnet_weights.pth?dl=0)
If you use this code, consider citing:
```
@inproceedings{Germain2020S2DNet,
title = {S2DNet: Learning Image Features for Accurate Sparse-to-Dense Matching},
author = {Hugo Germain and Guillaume Bourmaud and Vincent Lepetit},
booktitle = {European Conference on Computer Vision (ECCV)},
year = {2020}
}
```
Owner
- Login: MACILLAS
- Kind: user
- Location: Waterloo, Ontario-
- Company: CViSS Lab, Civil and Environmental Engineering, UWaterloo
- Website: maxmidwinter.ca
- Repositories: 2
- Profile: https://github.com/MACILLAS