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20232026
most citedAnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection

32 citations · 42 across the 15 of their papers we have counts for

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5 papers · 1 filter

cs.CV2024

Adaptive Deviation Learning for Visual Anomaly Detection with Data Contamination

Anindya Sundar Das, Guansong Pang, Monowar Bhuyan

Visual anomaly detection targets to detect images that notably differ from normal pattern, and it has found extensive application in identifying defective parts within the manufact…

cs.CV2024★ 2 cited

Toward Generalist Anomaly Detection via In-context Residual Learning with Few-shot Sample Prompts

Jiawen Zhu, Guansong Pang

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 d…

cs.CV2024

CoLeCLIP: Open-Domain Continual Learning via Joint Task Prompt and Vocabulary Learning

Yukun Li, Guansong Pang, Wei Suo +6

This paper explores the problem of continual learning (CL) of vision-language models (VLMs) in open domains, where the models need to perform continual updating and inference on a…

cs.CV2023★ 3 cited

Open-Vocabulary Video Anomaly Detection

Peng Wu, Xuerong Zhou, Guansong Pang +4

Video anomaly detection (VAD) with weak supervision has achieved remarkable performance in utilizing video-level labels to discriminate whether a video frame is normal or abnormal.…

cs.CV2023★ 32 cited

AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection

Qihang Zhou, Guansong Pang, Yu Tian +2

Zero-shot anomaly detection (ZSAD) requires detection models trained using auxiliary data to detect anomalies without any training sample in a target dataset. It is a crucial task…