14 citations · 40 across the 6 of their papers we have counts for
6 papers
Scale Attention for Learning Deep Face Representation: A Study Against Visual Scale Variation
Hailin Shi, Hang Du, Yibo Hu +3
Human face images usually appear with wide range of visual scales. The existing face representations pursue the bandwidth of handling scale variation via multi-scale scheme that as…
Boosting Semi-Supervised Face Recognition with Noise Robustness
Yuchi Liu, Hailin Shi, Hang Du +4
Although deep face recognition benefits significantly from large-scale training data, a current bottleneck is the labelling cost. A feasible solution to this problem is semi-superv…
Dive into Ambiguity: Latent Distribution Mining and Pairwise Uncertainty Estimation for Facial Expression Recognition
Jiahui She, Yibo Hu, Hailin Shi +3
Due to the subjective annotation and the inherent interclass similarity of facial expressions, one of key challenges in Facial Expression Recognition (FER) is the annotation ambigu…
FaceX-Zoo: A PyTorch Toolbox for Face Recognition
Jun Wang, Yinglu Liu, Yibo Hu +2
Deep learning based face recognition has achieved significant progress in recent years. Yet, the practical model production and further research of deep face recognition are in gre…
Semi-Siamese Training for Shallow Face Learning
Hang Du, Hailin Shi, Yuchi Liu +4
Most existing public face datasets, such as MS-Celeb-1M and VGGFace2, provide abundant information in both breadth (large number of IDs) and depth (sufficient number of samples) fo…
NPCFace: Negative-Positive Collaborative Training for Large-scale Face Recognition
Dan Zeng, Hailin Shi, Hang Du +3
The training scheme of deep face recognition has greatly evolved in the past years, yet it encounters new challenges in the large-scale data situation where massive and diverse har…