What Remains Normal? Clean Images Miss Useful Near-Defect Normal Patches for Anomaly Detection

arXiv:2608.23299 · cs.CV · Submitted 2026-08-24 · Read on arXiv

cs.CV

Submitted: 2026-08-24

Updated: 2026-09-18

Code: https://github.com/jw-chae/boundary_support

Terminology

• AUROC — 38× in this paper · explained in 2 episodes
• Core — 7× in this paper · explained in 2 episodes
• Computer Vision and Pattern Recognition — 6× in this paper
• Consistency — 5× in this paper · explained in 3 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Aggregation — 2× in this paper · explained in 1 episode
• Distillation — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• In International Conference on Learning Representations — 1× in this paper
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Self-Supervised Learning — 1× in this paper · explained in 8 episodes

Sources

• ProCon: Projection-Consistency Memory for Training-Free Anomaly Detection
• INP-Former++: Advancing Universal Anomaly Detection via Intrinsic Normal Prototypes and Residual Learning

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