Showing cs.CVShow all
2 papers · 1 filter
cs.CV2025
ViP-CLIP: Visual-Perception Prompting with Unified Alignment for Zero-Shot Anomaly Detection
Ziteng Yang, Jingzehua Xu, Yanshu Li +3
Zero-shot anomaly detection (ZSAD) aims to detect anomalies without any target domain training samples, relying solely on external auxiliary data. Existing CLIP-based methods attem…
cs.CV2025
LLaVA-RadZ: Can Multimodal Large Language Models Effectively Tackle Zero-shot Radiology Recognition?
Bangyan Li, Wenxuan Huang, Zhenkun Gao +8
Recently, Multimodal Large Language Models (MLLMs) have demonstrated exceptional capabilities in visual understanding and reasoning across various vision-language tasks. However, w…