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cs.CV2024
ALMRR: Anomaly Localization Mamba on Industrial Textured Surface with Feature Reconstruction and Refinement
Shichen Qu, Xian Tao, Zhen Qu +3
Unsupervised anomaly localization on industrial textured images has achieved remarkable results through reconstruction-based methods, yet existing approaches based on image reconst…
cs.CV2024
VCP-CLIP: A visual context prompting model for zero-shot anomaly segmentation
Zhen Qu, Xian Tao, Mukesh Prasad +4
Recently, large-scale vision-language models such as CLIP have demonstrated immense potential in zero-shot anomaly segmentation (ZSAS) task, utilizing a unified model to directly d…
cs.CV2024★ 1 cited
A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization
Qiyu Chen, Huiyuan Luo, Chengkan Lv +1
Anomaly synthesis strategies can effectively enhance unsupervised anomaly detection. However, existing strategies have limitations in the coverage and controllability of anomaly sy…