4 papers
SCOUT: Semi-supervised Camouflaged Object Detection by Utilizing Text and Adaptive Data Selection
Weiqi Yan, Lvhai Chen, Shengchuan Zhang +2
The difficulty of pixel-level annotation has significantly hindered the development of the Camouflaged Object Detection (COD) field. To save on annotation costs, previous works lev…
UCOD-DPL: Unsupervised Camouflaged Object Detection via Dynamic Pseudo-label Learning
Weiqi Yan, Lvhai Chen, Huaijia Kou +3
Unsupervised Camoflaged Object Detection (UCOD) has gained attention since it doesn't need to rely on extensive pixel-level labels. Existing UCOD methods typically generate pseudo-…
STeacher: Step-by-step Teacher for Sparsely Annotated Oriented Object Detection
Yu Lin, Jianghang Lin, Kai Ye +5
Although fully-supervised oriented object detection has made significant progress in multimodal remote sensing image understanding, it comes at the cost of labor-intensive annotati…
Breaking the Bias: Recalibrating the Attention of Industrial Anomaly Detection
Xin Chen, Liujuan Cao, Shengchuan Zhang +2
Due to the scarcity and unpredictable nature of defect samples, industrial anomaly detection (IAD) predominantly employs unsupervised learning. However, all unsupervised IAD method…