306 citations · 940 across the 27 of their papers we have counts for
27 papers
Twin Contrastive Learning with Noisy Labels
Zhizhong Huang, Junping Zhang, Hongming Shan
Learning from noisy data is a challenging task that significantly degenerates the model performance. In this paper, we present TCL, a novel twin contrastive learning model to learn…
CORE: Learning Consistent Ordinal REpresentations for Image Ordinal Estimation
Yiming Lei, Zilong Li, Yangyang Li +2
The goal of image ordinal estimation is to estimate the ordinal label of a given image with a convolutional neural network. Existing methods are mainly based on ordinal regression…
When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework and A New Benchmark
Zhizhong Huang, Junping Zhang, Hongming Shan
To minimize the impact of age variation on face recognition, age-invariant face recognition (AIFR) extracts identity-related discriminative features by minimizing the correlation b…
Motion Matters: A Novel Motion Modeling For Cross-View Gait Feature Learning
Jingqi Li, Jiaqi Gao, Yuzhen Zhang +2
As a unique biometric that can be perceived at a distance, gait has broad applications in person authentication, social security, and so on. Existing gait recognition methods suffe…
SAN-Net: Learning Generalization to Unseen Sites for Stroke Lesion Segmentation with Self-Adaptive Normalization
Weiyi Yu, Zhizhong Huang, Junping Zhang +1
There are considerable interests in automatic stroke lesion segmentation on magnetic resonance (MR) images in the medical imaging field, as stroke is an important cerebrovascular d…
Meta Ordinal Regression Forest for Medical Image Classification with Ordinal Labels
Yiming Lei, Haiping Zhu, Junping Zhang +1
The performance of medical image classification has been enhanced by deep convolutional neural networks (CNNs), which are typically trained with cross-entropy (CE) loss. However, w…