67 citations · 67 across the 2 of their papers we have counts for
6 papers
Deep face recognition with clustering based domain adaptation
Mei Wang, Weihong Deng
Despite great progress in face recognition tasks achieved by deep convolution neural networks (CNNs), these models often face challenges in real world tasks where training images g…
Meta Balanced Network for Fair Face Recognition
Mei Wang, Yaobin Zhang, Weihong Deng
Although deep face recognition has achieved impressive progress in recent years, controversy has arisen regarding discrimination based on skin tone, questioning their deployment in…
Mitigate Bias in Face Recognition using Skewness-Aware Reinforcement Learning
Mei Wang, Weihong Deng
Racial equality is an important theme of international human rights law, but it has been largely obscured when the overall face recognition accuracy is pursued blindly. More facts…
Racial Faces in-the-Wild: Reducing Racial Bias by Information Maximization Adaptation Network
Mei Wang, Weihong Deng, Jiani Hu +2
Racial bias is an important issue in biometric, but has not been thoroughly studied in deep face recognition. In this paper, we first contribute a dedicated dataset called Racial F…
Deep Face Recognition: A Survey
Mei Wang, Weihong Deng
Deep learning applies multiple processing layers to learn representations of data with multiple levels of feature extraction. This emerging technique has reshaped the research land…
Deep Visual Domain Adaptation: A Survey
Mei Wang, Weihong Deng
Deep domain adaption has emerged as a new learning technique to address the lack of massive amounts of labeled data. Compared to conventional methods, which learn shared feature su…