Toward generalist anomaly detection via in-context residual learning with few-shot sample prompts

• Main Authors: ZHU, Jiawen, PANG, Guansong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Generalist anomaly detection; Machine learning; Visual-language models; Artificial Intelligence and Robotics; Computer Sciences
• Online Access: https://ink.library.smu.edu.sg/sis_research/9762; https://ink.library.smu.edu.sg/context/sis_research/article/10762/viewcontent/2403.06495v3.pdf
• Institution: Singapore Management University

This paper explores the problem of Generalist Anomaly Detection (GAD), aiming to train one single detection model that can generalize to detect anomalies in diverse datasets from different application domains without any further training on the target data. Some recent studies have showed that large...