LogiCo is a unified framework using component-level feature reconstruction to detect both logical and structural anomalies, achieving SOTA results on four benchmarks with code publicly available.
arXiv preprint arXiv:2503.14910 (2025)
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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.
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LogiCo: A Unified Framework for Logical and Structural Anomaly Detection
LogiCo is a unified framework using component-level feature reconstruction to detect both logical and structural anomalies, achieving SOTA results on four benchmarks with code publicly available.
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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.