LUVLi and UGLLI Face Alignment
The code is officially available here
LUVLi Face Alignment: Estimating Landmarks' Location, Uncertainty, and Visibility Likelihood, CVPR 2020
[slides], [1min_talk], [supp],[demo]
UGLLI Face Alignment: Estimating Uncertainty with Gaussian Log-Likelihood Loss, ICCV Workshops on Statistical Deep Learning in Computer Vision 2019
[slides], [poster], [news], [Best Oral Presentation Award]
References
Please cite the following papers if you find this repository useful:
@inproceedings{kumar2020luvli,
title={LUVLi Face Alignment: Estimating Landmarks' Location, Uncertainty, and Visibility Likelihood},
author={Kumar, Abhinav and Marks, Tim K. and Mou, Wenxuan and Wang, Ye and Jones, Michael and Cherian, Anoop and Koike-Akino, Toshiaki and Liu, Xiaoming and Feng, Chen},
booktitle={IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2020}
}
@inproceedings{kumar2019uglli,
title={UGLLI Face Alignment: Estimating Uncertainty with Gaussian Log-Likelihood Loss},
author={Kumar, Abhinav and Marks, Tim K and Mou, Wenxuan and Feng, Chen and Liu, Xiaoming},
booktitle={ICCV Workshops on Statistical Deep Learning in Computer Vision},
year={2019}
}
Evaluation of our pre-trained models
| Split | Name | Directory | LUVLi | UGLLI |
|---|---|---|---|---|
| 1 | 300-W Split 1 | run_108 | lr-0.00002-49.pth.tar | - |
| 2 | 300-W Split 2 | run_109 | lr-0.00002-49.pth.tar | - |
| 3 | AFLW-19 | run_507 | lr-0.00002-49.pth.tar | - |
| 4 | WFLW | run_1005 | lr-0.00002-49.pth.tar | - |
| 5 | MERL-RAV (AFLW_ours) | run_5004 | lr-0.00002-49.pth.tar | - |
| 1 | 300-W Split 1 | run_924 | - | lr-0.00002-39.pth.tar |
| 2 | 300-W Split 2 | run_940 | - | lr-0.00002-39.pth.tar |
Copy the pre-trained models to the abhinav_model_dir first. The directory structure should look like this:
./FaceAlignmentUncertainty/
|--- abhinav_model_dir/
| |--- run_108
| | |--lr-0.00002-49.pth.tar
| |
| |--- run_109
| | |--lr-0.00002-49.pth.tar
| |
| |--- run_507
| | |--lr-0.00002-49.pth.tar
| |
| |--- run_1005
| | |--lr-0.00002-49.pth.tar
| |
| |--- run_5004
| | |--lr-0.00002-49.pth.tar
| ...
Next type the following:
./scripts_evaluation.shIn case you want to get our qualitative plots and also the transformed figures, type:
python plot/show_300W_images_overlaid_with_uncertainties.py --exp_id abhinav_model_dir/run_109_evaluate/ --laplacian
python plot/plot_uncertainties_in_transformed_space.py -i run_109_evaluate/300W_test --laplacian
python plot/plot_residual_covariance_vs_predicted_covariance.py -i run_109_evaluate --laplacian
python plot/plot_histogram_smallest_eigen_value.py -i run_109_evaluate --laplacian