6 citations · 23 across the 9 of their papers we have counts for
4 papers · 1 filter
All-to-key Attention for Arbitrary Style Transfer
Mingrui Zhu, Xiao He, Nannan Wang +2
Attention-based arbitrary style transfer studies have shown promising performance in synthesizing vivid local style details. They typically use the all-to-all attention mechanism -…
Improving Adversarial Robustness via Mutual Information Estimation
Dawei Zhou, Nannan Wang, Xinbo Gao +4
Deep neural networks (DNNs) are found to be vulnerable to adversarial noise. They are typically misled by adversarial samples to make wrong predictions. To alleviate this negative…
Towards Semi-Supervised Deep Facial Expression Recognition with An Adaptive Confidence Margin
Hangyu Li, Nannan Wang, Xi Yang +2
Only parts of unlabeled data are selected to train models for most semi-supervised learning methods, whose confidence scores are usually higher than the pre-defined threshold (i.e.…
Semi-parametric Makeup Transfer via Semantic-aware Correspondence
Mingrui Zhu, Yun Yi, Nannan Wang +2
The large discrepancy between the source non-makeup image and the reference makeup image is one of the key challenges in makeup transfer. Conventional approaches for makeup transfe…