UniVAD v2 improves 1N-shot mean image-level AUC from 83.0% to 84.5% (85.7% with one abnormal reference) via support-conditioned boundary construction on six datasets.
Provable optimal transport with transformers: The essence of depth and prompt engineering,
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UniVAD v2: Unified Visual Anomaly Detection via Support-Conditioned Boundary Construction
UniVAD v2 improves 1N-shot mean image-level AUC from 83.0% to 84.5% (85.7% with one abnormal reference) via support-conditioned boundary construction on six datasets.