8 citations · 8 across the 4 of their papers we have counts for
6 papers
Shadows can be Dangerous: Stealthy and Effective Physical-world Adversarial Attack by Natural Phenomenon
Yiqi Zhong, Xianming Liu, Deming Zhai +2
Estimating the risk level of adversarial examples is essential for safely deploying machine learning models in the real world. One popular approach for physical-world attacks is to…
Learning with Noisy Labels via Sparse Regularization
Xiong Zhou, Xianming Liu, Chenyang Wang +3
Learning with noisy labels is an important and challenging task for training accurate deep neural networks. Some commonly-used loss functions, such as Cross Entropy (CE), suffer fr…
Fully Unsupervised Person Re-identification viaSelective Contrastive Learning
Bo Pang, Deming Zhai, Junjun Jiang +1
Person re-identification (ReID) aims at searching the same identity person among images captured by various cameras. Unsupervised person ReID attracts a lot of attention recently,…
Single Image Deraining via Scale-space Invariant Attention Neural Network
Bo Pang, Deming Zhai, Junjun Jiang +1
Image enhancement from degradation of rainy artifacts plays a critical role in outdoor visual computing systems. In this paper, we tackle the notion of scale that deals with visual…
Rectified Meta-Learning from Noisy Labels for Robust Image-based Plant Disease Diagnosis
Ruifeng Shi, Deming Zhai, Xianming Liu +2
Plant diseases serve as one of main threats to food security and crop production. It is thus valuable to exploit recent advances of artificial intelligence to assist plant disease…
ADRN: Attention-based Deep Residual Network for Hyperspectral Image Denoising
Yongsen Zhao, Deming Zhai, Junjun Jiang +1
Hyperspectral image (HSI) denoising is of crucial importance for many subsequent applications, such as HSI classification and interpretation. In this paper, we propose an attention…