Browse State-of-the-Art › Anomaly Severity Classification (Anomaly vs. Defect)
Anomaly Severity Classification (Anomaly vs. Defect)
1 paper with code · 1 benchmark · 1 dataset archive 2025-07-28
Anomaly Severity Classification is a novel task that extends traditional anomaly detection by distinguishing between negligible anomalies and critical defects. While existing benchmarks focus on identifying whether an input deviates from normality, this task introduces a deployment-oriented perspective—evaluating the actionability of detected anomalies. For example, cosmetic deviations or design shifts may be acceptable (anomalies), while structural damages require intervention (defects). This task supports more informed and automated decision-making in industrial and quality control settings. It was introduced in the VELM paper, alongside a simulation benchmark derived from the MVTec-AC dataset.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| MVTec-AC (1 row) | VELM | Detect, Classify, Act: Categorizing Industrial Anomalies with... | code | — | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
1 dataset whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
1 shown of 1 paper with code (1 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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5 May 2025 1 repository listedRecent advances in visual industrial anomaly detection have demonstrated exceptional performance in identifying and segmenting anomalous regions while maintaining fast inference speeds.
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