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Multi-Domain Adversarial Feature Generalization for Person Re-Identification
Shan Lin, Chang-Tsun Li, Alex C. Kot
With the assistance of sophisticated training methods applied to single labeled datasets, the performance of fully-supervised person re-identification (Person Re-ID) has been impro…
Skeleton-based Relational Reasoning for Group Activity Analysis
Mauricio Perez, Jun Liu, Alex C. Kot
Research on group activity recognition mostly leans on the standard two-stream approach (RGB and Optical Flow) as their input features. Few have explored explicit pose information,…
Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization
Haoliang Li, YuFei Wang, Renjie Wan +3
Recently, we have witnessed great progress in the field of medical imaging classification by adopting deep neural networks. However, the recent advanced models still require access…
Feature Distillation With Guided Adversarial Contrastive Learning
Tao Bai, Jinnan Chen, Jun Zhao +3
Deep learning models are shown to be vulnerable to adversarial examples. Though adversarial training can enhance model robustness, typical approaches are computationally expensive.…
DRL-FAS: A Novel Framework Based on Deep Reinforcement Learning for Face Anti-Spoofing
Rizhao Cai, Haoliang Li, Shiqi Wang +2
Inspired by the philosophy employed by human beings to determine whether a presented face example is genuine or not, i.e., to glance at the example globally first and then carefull…
Heterogeneous Domain Generalization via Domain Mixup
Yufei Wang, Haoliang Li, Alex C. Kot
One of the main drawbacks of deep Convolutional Neural Networks (DCNN) is that they lack generalization capability. In this work, we focus on the problem of heterogeneous domain ge…