3 papers
cs.CV2023
Dual-Branch Reconstruction Network for Industrial Anomaly Detection with RGB-D Data
Chenyang Bi, Yueyang Li, Haichi Luo
Unsupervised anomaly detection methods are at the forefront of industrial anomaly detection efforts and have made notable progress. Previous work primarily used 2D information as i…
cs.IR2023
CL-Flow:Strengthening the Normalizing Flows by Contrastive Learning for Better Anomaly Detection
Shunfeng Wang, Yueyang Li, Haichi Luo +1
In the anomaly detection field, the scarcity of anomalous samples has directed the current research emphasis towards unsupervised anomaly detection. While these unsupervised anomal…
cs.CV2023
Semantic Feature Integration network for Fine-grained Visual Classification
Hui Wang, Yueyang li, Haichi Luo
Fine-Grained Visual Classification (FGVC) is known as a challenging task due to subtle differences among subordinate categories. Many current FGVC approaches focus on identifying a…