5 citations · 13 across the 6 of their papers we have counts for
4 papers
Domain Adaptation without Model Transferring
Kunhong Wu, Yucheng Shi, Yahong Han +3
In recent years, researchers have been paying increasing attention to the threats brought by deep learning models to data security and privacy, especially in the field of domain ad…
Analysis and Applications of Class-wise Robustness in Adversarial Training
Qi Tian, Kun Kuang, Kelu Jiang +2
Adversarial training is one of the most effective approaches to improve model robustness against adversarial examples. However, previous works mainly focus on the overall robustnes…
Unsupervised Domain Adaptation for Image Classification via Structure-Conditioned Adversarial Learning
Hui Wang, Jian Tian, Songyuan Li +4
Unsupervised domain adaptation (UDA) typically carries out knowledge transfer from a label-rich source domain to an unlabeled target domain by adversarial learning. In principle, e…
TapLab: A Fast Framework for Semantic Video Segmentation Tapping into Compressed-Domain Knowledge
Junyi Feng, Songyuan Li, Xi Li +4
Real-time semantic video segmentation is a challenging task due to the strict requirements of inference speed. Recent approaches mainly devote great efforts to reducing the model s…