QMUL-SurvFace: Surveillance Face Recognition Challenge
| Algorithm | Publication | TPIR@FPIR=30% | TPIR@FPIR=20% | TPIR@FPIR=10% | TPIR@FPIR=1% | AUC |
|---|---|---|---|---|---|---|
| CentreFace | ECCV 2016 | 27.3% | 21.0% | 13.8% | 3.1% | 37.3% |
| SphereFace | CVPR 2017 | 21.3% | 15.7% | 8.3% | 1.0% | 28.1% |
| FaceNet | CVPR 2015 | 12.7% | 8.1% | 4.3% | 1.0% | 19.8% |
| DeepID2 | NIPS 2014 | 12.8% | 8.1% | 3.4% | 0.8% | 20.8% |
| VggFace | BMVC 2015 | 6.5% | 4.8% | 2.5% | 0.2% | 9.6% |
1. CentreFace - Wen, Y., Zhang, K., Li, Z., & Qiao, Y. (2016, October). A discriminative feature learning approach for deep face recognition. In European Conference on Computer Vision (pp. 499-515). Springer, Cham.
2. SphereFace - Liu, W., Wen, Y., Yu, Z., Li, M., Raj, B., & Song, L. (2017, July). Sphereface: Deep hypersphere embedding for face recognition. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Vol. 1).
3. FaceNet - Schroff, F., Kalenichenko, D., & Philbin, J. (2015). Facenet: A unified embedding for face recognition and clustering. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 815-823).
4. DeepID2 - Sun, Y., Chen, Y., Wang, X., & Tang, X. (2014). Deep learning face representation by joint identification-verification. In Advances in neural information processing systems (pp. 1988-1996).
5. VggFace - Parkhi, O. M., Vedaldi, A., & Zisserman, A. (2015, September). Deep Face Recognition. In BMVC (Vol. 1, No. 3, p. 6).
| Algorithm | Publication | TAR@FAR=30% | TAR@FAR=10% | TAR@FAR=1% | TAR@FAR=0.1% | AUC | Ave. Accuracy |
|---|---|---|---|---|---|---|---|
| CentreFace | ECCV 2016 | 95.2% | 86.0% | 53.3% | 26.8% | 94.8% | 88.0% |
| FaceNet | CVPR 2015 | 94.6% | 79.9% | 40.3% | 12.7% | 93.5% | 85.3% |
| DeepID2 | NIPS 2014 | 80.6% | 60.0% | 28.2% | 13.4% | 84.1% | 76.1% |
| SphereFace | CVPR 2017 | 80.0% | 63.6% | 34.1% | 15.6% | 83.9% | 77.6% |
| VggFace | BMVC 2015 | 83.2% | 63.0% | 20.1% | 4.0% | 85.0% | 78.0% |
1. CentreFace - Wen, Y., Zhang, K., Li, Z., & Qiao, Y. (2016, October). A discriminative feature learning approach for deep face recognition. In European Conference on Computer Vision (pp. 499-515). Springer, Cham.
2. FaceNet - Schroff, F., Kalenichenko, D., & Philbin, J. (2015). Facenet: A unified embedding for face recognition and clustering. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 815-823).
3. DeepID2 - Sun, Y., Chen, Y., Wang, X., & Tang, X. (2014). Deep learning face representation by joint identification-verification. In Advances in neural information processing systems (pp. 1988-1996).
4. SphereFace - Liu, W., Wen, Y., Yu, Z., Li, M., Raj, B., & Song, L. (2017, July). Sphereface: Deep hypersphere embedding for face recognition. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Vol. 1).
5. VggFace - Parkhi, O. M., Vedaldi, A., & Zisserman, A. (2015, September). Deep Face Recognition. In BMVC (Vol. 1, No. 3, p. 6).