Facial Action Unit Detection on BP4D (test)
0.668Average F1 ScoreUAU-Net
Evaluation results
| Method | Links | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| UAU-Net2026.04 | 0.668 | — | — | — | 0.579 | 0.513 | 0.619 | 0.799 | 0.789 | 0.859 | 0.888 | 0.659 | 0.563 | 0.644 | 0.513 | 0.601 | |
| MDHR2026.04 | 0.666 | — | — | — | 0.583 | 0.509 | 0.589 | 0.784 | 0.803 | 0.849 | 0.882 | 0.695 | 0.56 | 0.655 | 0.495 | 0.593 | |
| AUNCE2026.04 | 0.661 | — | — | — | 0.536 | 0.498 | 0.616 | 0.784 | 0.788 | 0.847 | 0.896 | 0.674 | 0.551 | 0.654 | 0.509 | 0.58 | |
| WSRTL2026.04 | 0.659 | — | — | — | 0.597 | 0.517 | 0.616 | 0.803 | 0.809 | 0.852 | 0.897 | 0.678 | 0.522 | 0.634 | 0.514 | 0.469 | |
| SACL2026.04 | 0.656 | — | — | — | 0.578 | 0.488 | 0.594 | 0.791 | 0.788 | 0.84 | 0.882 | 0.652 | 0.561 | 0.638 | 0.508 | 0.552 | |
| AU-TTT2026.04 | 0.656 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| ME-GraphAU2026.04 | 0.655 | — | — | — | 0.527 | 0.443 | 0.609 | 0.799 | 0.801 | 0.853 | 0.892 | 0.694 | 0.554 | 0.644 | 0.498 | 0.551 | |
| RETD2026.04 | 0.651 | — | — | — | 0.547 | 0.508 | 0.571 | 0.788 | 0.796 | 0.846 | 0.88 | 0.67 | 0.549 | 0.629 | 0.486 | 0.545 | |
| SMA-Net2026.04 | 0.65 | — | — | — | 0.565 | 0.451 | 0.57 | 0.795 | 0.795 | 0.845 | 0.864 | 0.661 | 0.558 | 0.642 | 0.487 | 0.568 | |
| HSTR-Net2026.04 | 0.647 | — | — | — | 0.555 | 0.495 | 0.619 | 0.766 | 0.802 | 0.842 | 0.874 | 0.626 | 0.548 | 0.641 | 0.471 | 0.521 | |
| AC2D2026.04 | 0.646 | — | — | — | 0.542 | 0.547 | 0.565 | 0.77 | 0.762 | 0.84 | 0.89 | 0.636 | 0.548 | 0.636 | 0.465 | 0.548 | |
| UGN2026.04 | 0.633 | — | — | — | 0.542 | 0.464 | 0.568 | 0.762 | 0.767 | 0.824 | 0.861 | 0.647 | 0.512 | 0.631 | 0.485 | 0.536 | |
| SRERL2026.04 | 0.629 | — | — | — | 0.469 | 0.453 | 0.556 | 0.771 | 0.784 | 0.835 | 0.876 | 0.639 | 0.522 | 0.639 | 0.471 | 0.533 | |
| ARL2026.04 | 0.612 | — | — | — | 0.458 | 0.398 | 0.551 | 0.757 | 0.772 | 0.823 | 0.866 | 0.588 | 0.476 | 0.621 | 0.474 | 0.554 | |
| JAA-Net2026.04 | 0.6 | — | — | — | 0.472 | 0.44 | 0.549 | 0.775 | 0.746 | 0.84 | 0.869 | 0.619 | 0.436 | 0.603 | 0.427 | 0.419 | |
| EAC-Net2026.04 | 0.556 | — | — | — | 0.39 | 0.352 | 0.486 | 0.761 | 0.729 | 0.819 | 0.862 | 0.588 | 0.375 | 0.591 | 0.359 | 0.358 | |
| CPM2018.03 | — | 0.5 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| DRML2018.03 | — | 0.483 | 0.56 | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| EAC-Net2018.03 | — | 0.559 | 0.752 | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| FERA 2015 Baseline2019.09 | — | — | — | 0.53 | — | — | — | — | — | — | — | — | — | — | — | — | |
| FERA 2015 Winner2019.09 | — | — | — | 0.54 | — | — | — | — | — | — | — | — | — | — | — | — | |
| JAA-Net2018.03 | — | 0.6 | 0.784 | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| JPML2018.03 | — | 0.459 | 0.505 | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| LSVM2018.03 | — | 0.353 | 0.322 | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| MT-VGGTraining Database=Aff-Wild22019.09 | — | — | — | 0.66 | — | — | — | — | — | — | — | — | — | — | — | — | |
| ROI2018.03 | — | 0.564 | — | — | — | — | — | — | — | — | — | — | — | — | — | — |