5 citations · 5 across the 3 of their papers we have counts for
4 papers
Towards Efficient Pixel Labeling for Industrial Anomaly Detection and Localization
Jingqi Wu, Hanxi Li, Lin Yuanbo Wu +3
Industrial product inspection is often performed using Anomaly Detection (AD) frameworks trained solely on non-defective samples. Although defective samples can be collected during…
Towards Efficient Pixel Labeling for Industrial Anomaly Detection and Localization
Hanxi Li, Jingqi Wu, Lin Yuanbo Wu +3
In the realm of practical Anomaly Detection (AD) tasks, manual labeling of anomalous pixels proves to be a costly endeavor. Consequently, many AD methods are crafted as one-class c…
A Novel Approach to Industrial Defect Generation through Blended Latent Diffusion Model with Online Adaptation
Hanxi Li, Zhengxun Zhang, Hao Chen +4
Effectively addressing the challenge of industrial Anomaly Detection (AD) necessitates an ample supply of defective samples, a constraint often hindered by their scarcity in indust…
Boosting Box-supervised Instance Segmentation with Pseudo Depth
Xinyi Yu, Ling Yan, Pengtao Jiang +4
The realm of Weakly Supervised Instance Segmentation (WSIS) under box supervision has garnered substantial attention, showcasing remarkable advancements in recent years. However, t…