3 papers
cs.CV2024
Dual-Image Enhanced CLIP for Zero-Shot Anomaly Detection
Zhaoxiang Zhang, Hanqiu Deng, Jinan Bao +1
Image Anomaly Detection has been a challenging task in Computer Vision field. The advent of Vision-Language models, particularly the rise of CLIP-based frameworks, has opened new a…
eess.IV2024
BMAD: Benchmarks for Medical Anomaly Detection
Jinan Bao, Hanshi Sun, Hanqiu Deng +3
Anomaly detection (AD) is a fundamental research problem in machine learning and computer vision, with practical applications in industrial inspection, video surveillance, and medi…
cs.CV2024
Bootstrap Fine-Grained Vision-Language Alignment for Unified Zero-Shot Anomaly Localization
Hanqiu Deng, Zhaoxiang Zhang, Jinan Bao +1
Contrastive Language-Image Pre-training (CLIP) models have shown promising performance on zero-shot visual recognition tasks by learning visual representations under natural langua…