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One-class CIFAR-10 Benchmark (Anomaly Detection)
Anomaly Detection is a binary classification identifying unusual or unexpected patterns in a dataset, which deviate significantly from the majority of the data. The goal of anomaly detection is to identify such anomalies, which could represent errors, fraud, or other types of unusual events, and flag them for further investigation.
[Image source]: GAN-based Anomaly Detection in Imbalance Problems
The archive carries no text for this table; the description above is the archive's text for the task Anomaly Detection. archive 2025-07-28
Over time archive 2025-07-28
The chart needs JavaScript; the table below carries every value.
Not inferred: AUROC. Points are placed at the row's paper date; 36 of 36 rows carry one.
Results archive 2025-07-28
Archive rows end at the archive snapshot, 2025-07-28: no result published after that date is in this table. Rank is the archive's row order at that snapshot; not re-ranked here. Metric values are the archive's strings. Column headers sort the table in your browser; each row keeps its archive rank.
| Paper | Code | Ran Syntology | Report | |||||
|---|---|---|---|---|---|---|---|---|
| 1 | CLIP (OE) | 99.6 | ✓ | Paper | Code | 2022 | 0 of 1 ran · 1 unverified | report |
| 2 | GeneralAD | 99.3 | – | Paper | Code | 2024 | 3 of 4 ran · 1 unverified | report |
| 3 | Fake It Till You Make It | 99.1 | ✓ | Paper | Code | 2022 | linked, not harvested | report |
| 4 | BLISS | 99.1 | – | Paper | – | 2024 | no code linked | report |
| 5 | PANDA-OE | 98.9 | ✓ | Paper | Code | 2020 | linked, not harvested | report |
| 6 | Mean-Shifted Contrastive Loss | 98.6 | ✓ | Paper | Code | 2021 | linked, not harvested | report |
| 7 | CLIP (zero shot) | 98.5 | – | Paper | Code | 2022 | 0 of 1 ran · 1 unverified | report |
| 8 | DINO-FT | 98.4 | – | Paper | Code | 2022 | linked, not harvested | report |
| 9 | Transformaly | 98.3 | ✓ | Paper | Code | 2021 | linked, not harvested | report |
| 10 | CAP | 97.0 | – | Paper | Code | 2021 | linked, not harvested | report |
| 11 | PANDA | 96.2 | – | Paper | Code | 2020 | linked, not harvested | report |
| 12 | CSI | 94.3 | – | Paper | Code | 2020 | 1 of 1 ran · 0 unverified | report |
| 13 | DUIAD | 92.6 | – | Paper | – | 2020 | no code linked | report |
| 14 | DN2 | 92.5 | ✓ | Paper | – | 2020 | no code linked | report |
| 15 | DisAug CLR | 92.5 | – | Paper | Code | 2020 | linked, not harvested | report |
| 16 | FCDD | 92 | ✓ | Paper | Code | 2020 | 0 of 1 ran · 1 unverified | report |
| 17 | IGD (pre-trained SSL) | 91.25 | – | Paper | Code | 2021 | 1 of 1 ran · 0 unverified | report |
| 18 | GAN based Anomaly Detection in Imbalance Problems | 90.6 | ✓ | Paper | – | 2020 | no code linked | report |
| 19 | SSOOD | 90.1 | – | Paper | Code | 2019 | 5 of 12 ran · 7 unverified | report |
| 20 | SSD | 90.0 | – | Paper | Code | 2021 | 1 of 1 ran · 0 unverified | report |
| 21 | UTAD | 88.4 | – | Paper | – | 2021 | no code linked | report |
| 22 | GOAD | 88.2 | – | Paper | Code | 2020 | 5 of 10 ran · 5 unverified | report |
| 23 | ARNET | 86.6 | – | Paper | Code | 2019 | linked, not harvested | report |
| 24 | Reverse Distillation | 86.5 | – | Paper | Code | 2022 | 14 of 18 ran · 4 unverified | report |
| 25 | ADT | 86 | – | Paper | Code | 2018 | 0 of 5 ran · 5 unverified | report |
| 26 | IGD (pre-trained ImageNet) | 83.68 | – | Paper | Code | 2021 | 1 of 1 ran · 0 unverified | report |
| 27 | ESAD | 83.3 | ✓ | Paper | – | 2020 | no code linked | report |
| 28 | IGD (scratch) | 74.33 | – | Paper | Code | 2021 | 1 of 1 ran · 0 unverified | report |
| 29 | P-KDGAN | 73.05 | – | Paper | – | 2020 | no code linked | report |
| 30 | OLED | 67.1 | – | Paper | Code | 2021 | linked, not harvested | report |
| 31 | OCGAN | 66.83 | – | Paper | – | 2019 | no code linked | report |
| 32 | FastFlow | 66.7 | – | Paper | Code | 2021 | 0 of 6 ran · 6 unverified | report |
| 33 | DASVDD | 66.5 | – | Paper | Code | 2021 | 2 of 2 ran · 0 unverified | report |
| 34 | Deep SVDD | 65.7 | – | Paper | Code | 2018 | linked, not harvested | report |
| 35 | Self-Supervised DeepSVDD | 64.8 | – | Paper | Code | 2020 | linked, not harvested | report |
| 36 | Self-Supervised One-class SVM, RBF kernel | 64.7 | – | Paper | Code | 2020 | linked, not harvested | report |
All 36 rows shown. 36 link to a paper page on this site; 9 are marked as using additional training data in the archive. No GitHub stars are tracked; "Code" is the first repository the archive lists for the row. The archive carries no row tags, review links or community-submitted rows for this table; none are shown. archive 2025-07-28
Syntology Ran reads "N of M ran · U unverified": of the M code samples Syntology harvested from repositories linked to that row's paper (joined by arXiv id), N executed on a synthesized input and the other U = M−N are unverified (harvested, no recorded run). It counts code from repositories linked to that row's paper, not this result: the row's number was not reproduced and nothing here is a correctness claim. The other cell texts mean no graph line for the row: "linked, not harvested" (the archive links code, Syntology has not harvested it), "no code linked" (no code link in the archive), "not matched" (the row's paper URL matched no paper on this site). 15 rows have a graph line, from 12 distinct papers; 10 rows (8 papers) have at least one sample that ran. Counting each paper once: Syntology ran 32 of 62 samples; 30 unverified. Separately, 23 of those 62 are pointer-only (licence): the site points at that code rather than redistributing it, a licence property recorded for ran and unverified samples alike; each cell's tooltip carries the row's own pointer-only count. Read from the graph 2026-09-24. Per-sample status is on the paper page.
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