Awesome
Heatmap Regression via Randomized Rounding
[2020/09/02]: the paper is available on ArXiv.
[2020/10/28]: add new models for 106 facial landmarks.
[2021/09/21]: add new models for 68 facial landmarks (see models/README.md).
Introduction
This repo contains the facial landmark detection code for "Heatmap Regression via Randomized Rounding".
Demo
export PYTHONPATH=./:$PYTHONPATH
python examples/demo.py --image data/demo.jpg --model models/wflw/hrnet18_256x256_p2/
Test on WFLW (98 facial landmarks)
python examples/test_wflw.py --model models/wflw/hrnet18_256x256_p1/
| Backbone | BBox | Resolution | #Params | FLOPs | NME (%) |
|---|---|---|---|---|---|
| HRNet-W18 | P1 | 256x256 | 9.69M | 4.84G | 3.81 |
| HRNet-W18 | P2 | 256x256 | 9.69M | 4.84G | 3.95 |
| MobileNetV2 | P2 | 256x256 | 0.60M | 0.51G | 4.45 |
| MobileNetV2 | P2 | 160x160 | 0.60M | 0.20G | 4.58 |
| MobileNetV2 | P2 | 128x128 | 0.60M | 0.13G | 4.72 |
Test on LaPa (106 facial landmarks)
python examples/test_lapa.py --model models/lapa/hrnet18_256x256_p2/
| Backbone | BBox | Resolution | #Params | FLOPs | NME (%) |
|---|---|---|---|---|---|
| HRNet-W18 | P2 | 256x256 | 9.69M | 4.86G | 1.40 |
| MobileNetV2 | P2 | 256x256 | 0.60M | 0.52G | 1.69 |
| MobileNetV2 | P2 | 128x128 | 0.60M | 0.13G | 2.08 |
NOTE：All pretrained models can also be downloaded from google drive.
Citation
@article{yu2021heatmap,
title={Heatmap Regression via Randomized Rounding},
author={Yu, Baosheng and Tao, Dacheng},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
year={2021}
}
Contact
Baosheng Yu, baosheng.yu.usyd@gmail.com.