84 citations · 152 across the 7 of their papers we have counts for
6 papers · 1 filter
Improving Training and Inference of Face Recognition Models via Random Temperature Scaling
Lei Shang, Mouxiao Huang, Wu Shi +6
Data uncertainty is commonly observed in the images for face recognition (FR). However, deep learning algorithms often make predictions with high confidence even for uncertain or i…
HSVA: Hierarchical Semantic-Visual Adaptation for Zero-Shot Learning
Shiming Chen, Guo-Sen Xie, Yang Liu +5
Zero-shot learning (ZSL) tackles the unseen class recognition problem, transferring semantic knowledge from seen classes to unseen ones. Typically, to guarantee desirable knowledge…
Digging into Uncertainty in Self-supervised Multi-view Stereo
Hongbin Xu, Zhipeng Zhou, Yali Wang +4
Self-supervised Multi-view stereo (MVS) with a pretext task of image reconstruction has achieved significant progress recently. However, previous methods are built upon intuitions,…
Learning to Cluster Faces via Transformer
Jinxing Ye, Xioajiang Peng, Baigui Sun +4
Face clustering is a useful tool for applications like automatic face annotation and retrieval. The main challenge is that it is difficult to cluster images from the same identity…
AU-Guided Unsupervised Domain Adaptive Facial Expression Recognition
Kai Wang, Yuxin Gu, Xiaojiang Peng +3
The domain diversities including inconsistent annotation and varied image collection conditions inevitably exist among different facial expression recognition (FER) datasets, which…
SoftTriple Loss: Deep Metric Learning Without Triplet Sampling
Qi Qian, Lei Shang, Baigui Sun +3
Distance metric learning (DML) is to learn the embeddings where examples from the same class are closer than examples from different classes. It can be cast as an optimization prob…