visual anomaly detection

AdaptCLIP: Adapting CLIP for Universal Visual Anomaly Detection AAAI 2026 AnomalyMoE: Towards a Language-free Generalist Model for Unified Visual Anomaly Detection AAAI 2026 Adaptive Deviation Learning for Visual Anomaly Detection with Data Contamination WACV 2025 Boosting Fine-Grained Visual Anomaly Detection with Coarse-Knowledge-Aware Adversarial Learning AAAI 2025 CAVE : Detecting and Explaining Commonsense Anomalies in Visual Environments EMNLP 2025 ReMP-AD: Retrieval-enhanced Multi-modal Prompt Fusion for Few-Shot Industrial Visual Anomaly Detection ICCV 2025 ROADS: Robust Prompt-Driven Multi-Class Anomaly Detection under Domain Shift WACV 2025 Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models CVPR 2025 UniVAD: A Training-free Unified Model for Few-shot Visual Anomaly Detection CVPR 2025 Unseen Visual Anomaly Generation CVPR 2025 Vision-Language Models Can't See the Obvious ICCV 2025 Attention Modules Improve Image-Level Anomaly Detection for Industrial Inspection: A DifferNet Case Study WACV 2024 CableInspect-AD: An Expert-Annotated Anomaly Detection Dataset NeurIPS 2024 One-for-All: Proposal Masked Cross-Class Anomaly Detection AAAI 2023