197 citations · 279 across the 11 of their papers we have counts for
Showing 2024Show all
3 papers · 1 filter
cs.CV2024
SAM-SP: Self-Prompting Makes SAM Great Again
Chunpeng Zhou, Kangjie Ning, Qianqian Shen +3
The recently introduced Segment Anything Model (SAM), a Visual Foundation Model (VFM), has demonstrated impressive capabilities in zero-shot segmentation tasks across diverse natur…
cs.LG2024
Towards a Unified Framework of Clustering-based Anomaly Detection
Zeyu Fang, Ming Gu, Sheng Zhou +4
Unsupervised Anomaly Detection (UAD) plays a crucial role in identifying abnormal patterns within data without labeled examples, holding significant practical implications across v…
cs.LG2024★ 2 cited
Guarding Graph Neural Networks for Unsupervised Graph Anomaly Detection
Yuanchen Bei, Sheng Zhou, Jinke Shi +3
Unsupervised graph anomaly detection aims at identifying rare patterns that deviate from the majority in a graph without the aid of labels, which is important for a variety of real…