The recent rapid development of deep learning has laid a milestone in industrial image
anomaly detection (IAD). In this paper, we provide a comprehensive review of deep learning …

Large language models (LLMs) have revolutionized natural language processing with their
exceptional understanding, synthesizing, and reasoning capabilities. However, deploying …

Large Vision-Language Models (LVLMs) such as MiniGPT-4 and LLaVA have demonstrated
the capability of understanding images and achieved remarkable performance in various …

Reconstruction-based approaches have achieved remarkable outcomes in anomaly
detection. The exceptional image reconstruction capabilities of recently popular diffusion …

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 …

Recent advancements in large-scale visual-language pre-trained models have led to
significant progress in zero-/few-shot anomaly detection within natural image domains …

The vision-language model has brought great improvement to few-shot industrial anomaly
detection which usually needs to design of hundreds of prompts through prompt …

Anomaly inspection plays an important role in industrial manufacture. Existing anomaly
inspection methods are limited in their performance due to insufficient anomaly data …

We study the zero-shot Composed Image Retrieval (ZS-CIR) task which is to retrieve the
target image given a reference image and a description without training on the triplet …

We present a novel framework, ie, Segment Any Anomaly+(SAA+), for zero-shot anomaly
segmentation with hybrid prompt regularization to improve the adaptability of modern …