6 papers
Collaborative Reconstruction and Repair for Multi-class Industrial Anomaly Detection
Qishan Wang, Haofeng Wang, Shuyong Gao +5
Industrial anomaly detection is a challenging open-set task that aims to identify unknown anomalous patterns deviating from normal data distribution. To avoid the significant memor…
MSVCOD:A Large-Scale Multi-Scene Dataset for Video Camouflage Object Detection
Shuyong Gao, Yu'ang Feng, Qishan Wang +5
Video Camouflaged Object Detection (VCOD) is a challenging task which aims to identify objects that seamlessly concealed within the background in videos. The dynamic properties of…
Search is All You Need for Few-shot Anomaly Detection
Qishan Wang, Jia Guo, Shuyong Gao +5
Few-shot anomaly detection (FSAD) has emerged as a crucial yet challenging task in industrial inspection, where normal distribution modeling must be accomplished with only a few no…
HSS-IAD: A Heterogeneous Same-Sort Industrial Anomaly Detection Dataset
Qishan Wang, Shuyong Gao, Junjie Hu +4
Multi-class Unsupervised Anomaly Detection algorithms (MUAD) are receiving increasing attention due to their relatively low deployment costs and improved training efficiency. Howev…
AnimatePainter: A Self-Supervised Rendering Framework for Reconstructing Painting Process
Junjie Hu, Shuyong Gao, Qianyu Guo +4
Humans can intuitively decompose an image into a sequence of strokes to create a painting, yet existing methods for generating drawing processes are limited to specific data types…
P3S-Diffusion:A Selective Subject-driven Generation Framework via Point Supervision
Junjie Hu, Shuyong Gao, Lingyi Hong +4
Recent research in subject-driven generation increasingly emphasizes the importance of selective subject features. Nevertheless, accurately selecting the content in a given referen…