most citedLearning Fair Face Representation With Progressive Cross Transformer

10 citations · 26 across the 4 of their papers we have counts for

collaborators

7 papers

cs.NI20213 cited

Going Deeper in Frequency Convolutional Neural Network: A Theoretical Perspective

Xiaohan Zhu, Zhen Cui, Tong Zhang +2

Convolutional neural network (CNN) is one of the most widely-used successful architectures in the era of deep learning. However, the high-computational cost of CNN still hampers mo…

cs.CV202110 cited

Learning Fair Face Representation With Progressive Cross Transformer

Yong Li, Yufei Sun, Zhen Cui +2

Face recognition (FR) has made extraordinary progress owing to the advancement of deep convolutional neural networks. However, demographic bias among different racial cohorts still…

cs.CV20214 cited

Consistent Instance False Positive Improves Fairness in Face Recognition

Xingkun Xu, Yuge Huang, Pengcheng Shen +5

Demographic bias is a significant challenge in practical face recognition systems. Existing methods heavily rely on accurate demographic annotations. However, such annotations are…

cs.CV2021

Meta Auxiliary Learning for Facial Action Unit Detection

Yong Li, Shiguang Shan

Despite the success of deep neural networks on facial action unit (AU) detection, better performance depends on a large number of training images with accurate AU annotations. Howe…

cs.CV2021

Learning Normal Dynamics in Videos with Meta Prototype Network

Hui Lv, Chen Chen, Zhen Cui +3

Frame reconstruction (current or future frame) based on Auto-Encoder (AE) is a popular method for video anomaly detection. With models trained on the normal data, the reconstructio…

cs.CV20219 cited

SDD-FIQA: Unsupervised Face Image Quality Assessment with Similarity Distribution Distance

Fu-Zhao Ou, Xingyu Chen, Ruixin Zhang +6

In recent years, Face Image Quality Assessment (FIQA) has become an indispensable part of the face recognition system to guarantee the stability and reliability of recognition perf…