52 citations · 73 across the 5 of their papers we have counts for
6 papers
Visual Anomaly Detection for Images: A Survey
Jie Yang, Ruijie Xu, Zhiquan Qi +1
Visual anomaly detection is an important and challenging problem in the field of machine learning and computer vision. This problem has attracted a considerable amount of attention…
Fast and Accurate Road Crack Detection Based on Adaptive Cost-Sensitive Loss Function
Kai Li, Bo Wang, Yingjie Tian +1
Numerous detection problems in computer vision, including road crack detection, suffer from exceedingly foreground-background imbalance. Fortunately, modification of loss function…
Two-stage Training for Learning from Label Proportions
Jiabin Liu, Bo Wang, Xin Shen +2
Learning from label proportions (LLP) aims at learning an instance-level classifier with label proportions in grouped training data. Existing deep learning based LLP methods utiliz…
Concatenated Attention Neural Network for Image Restoration
Tian YingJie, Wang YiQi, Yang LinRui +1
In this paper, we present a general framework for low-level vision tasks including image compression artifacts reduction and image denoising. Under this framework, a novel concaten…
Learning to Incorporate Structure Knowledge for Image Inpainting
Jie Yang, Zhiquan Qi, Yong Shi
This paper develops a multi-task learning framework that attempts to incorporate the image structure knowledge to assist image inpainting, which is not well explored in previous wo…
Learning from Label Proportions with Generative Adversarial Networks
Jiabin Liu, Bo Wang, Zhiquan Qi +2
In this paper, we leverage generative adversarial networks (GANs) to derive an effective algorithm LLP-GAN for learning from label proportions (LLP), where only the bag-level propo…