71 citations · 105 across the 11 of their papers we have counts for
6 papers · 1 filter
MixPro: Data Augmentation with MaskMix and Progressive Attention Labeling for Vision Transformer
Qihao Zhao, Yangyu Huang, Wei Hu +2
The recently proposed data augmentation TransMix employs attention labels to help visual transformers (ViT) achieve better robustness and performance. However, TransMix is deficien…
FreeEnricher: Enriching Face Landmarks without Additional Cost
Yangyu Huang, Xi Chen, Jongyoo Kim +4
Recent years have witnessed significant growth of face alignment. Though dense facial landmark is highly demanded in various scenarios, e.g., cosmetic medicine and facial beautific…
General Facial Representation Learning in a Visual-Linguistic Manner
Yinglin Zheng, Hao Yang, Ting Zhang +7
How to learn a universal facial representation that boosts all face analysis tasks? This paper takes one step toward this goal. In this paper, we study the transfer performance of…
ADNet: Leveraging Error-Bias Towards Normal Direction in Face Alignment
Yangyu Huang, Hao Yang, Chong Li +2
The recent progress of CNN has dramatically improved face alignment performance. However, few works have paid attention to the error-bias with respect to error distribution of faci…
P-DIFF: Learning Classifier with Noisy Labels based on Probability Difference Distributions
Wei Hu, QiHao Zhao, Yangyu Huang +1
Learning deep neural network (DNN) classifier with noisy labels is a challenging task because the DNN can easily over-fit on these noisy labels due to its high capability. In this…
Noise-Tolerant Paradigm for Training Face Recognition CNNs
Wei Hu, Yangyu Huang, Fan Zhang +1
Benefit from large-scale training datasets, deep Convolutional Neural Networks(CNNs) have achieved impressive results in face recognition(FR). However, tremendous scale of datasets…