Segment-Any-Anomaly
Explore a new approach to zero-shot anomaly segmentation without additional training through hybrid prompt regularization combined with existing foundation models. Improve anomaly detection using models like Grounding DINO and Segment Anything. This repository features user-friendly demos available on Colab and Huggingface, showcasing the efficacy of the SAA+ framework on datasets such as MVTec-AD, VisA, KSDD2, and MTD. SAA+ provides optimal anomaly identification with minimal setup, catering to computer vision researchers and developers. Discover recent advancements and the work that led to success at the VAND workshop.
