Browse › Computer Vision › Data Augmentation › ImageNet
ImageNet Benchmark (Data Augmentation)
Data augmentation involves techniques used for increasing the amount of data, based on different modifications, to expand the amount of examples in the original dataset. Data augmentation not only helps to grow the dataset but it also increases the diversity of the dataset. When training machine learning models, data augmentation acts as a regularizer and helps to avoid overfitting.
Data augmentation techniques have been found useful in domains like NLP and computer vision. In computer vision, transformations like cropping, flipping, and rotation are used. In NLP, data augmentation techniques can include swapping, deletion, random insertion, among others.
Further readings:
The archive carries no text for this table; the description above is the archive's text for the task Data Augmentation. archive 2025-07-28
Over time archive 2025-07-28
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Direction inferred from the metric name, not from the archive: Accuracy (%) (higher is better). Points are placed at the row's paper date; 17 of 17 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 | DeiT-B (+MixPro) | 82.9 | – | Paper | Code | 2023 | 10 of 18 ran · 8 unverified | report |
| 2 | ResNet-200 (DeepAA) | 81.32 | – | Paper | Code | 2022 | linked, not harvested | report |
| 3 | DeiT-S (+MixPro) | 81.3 | – | Paper | Code | 2023 | 10 of 18 ran · 8 unverified | report |
| 4 | ResNet-200 (Fast AA) | 80.6 | – | Paper | Code | 2019 | 22 of 40 ran · 18 unverified | report |
| 5 | ResNet-200 (UA) | 80.4 | – | Paper | Code | 2020 | linked, not harvested | report |
| 6 | ResNet-200 (AA) | 80.0 | – | Paper | Code | 2018 | 6 of 43 ran · 37 unverified | report |
| 7 | ResNet-50 (DeepAA) | 78.30 | – | Paper | Code | 2022 | linked, not harvested | report |
| 8 | ResNet-50 (TA wide) | 78.07 | – | Paper | Code | 2021 | linked, not harvested | report |
| 9 | ResNet-50 (LoRot-E) | 77.72 | – | Paper | Code | 2022 | 0 of 1 ran · 1 unverified | report |
| 10 | ResNet-50 (LoRot-I) | 77.71 | – | Paper | Code | 2022 | 0 of 1 ran · 1 unverified | report |
| 11 | ResNet-50 (UA) | 77.63 | – | Paper | Code | 2020 | linked, not harvested | report |
| 12 | ResNet-50 (AA) | 77.6 | – | Paper | Code | 2018 | 6 of 43 ran · 37 unverified | report |
| 13 | ResNet-50 (Fast AA) | 77.6 | – | Paper | Code | 2019 | 22 of 40 ran · 18 unverified | report |
| 14 | ResNet-50 (RA) | 77.6 | – | Paper | Code | 2019 | 58 of 65 ran · 7 unverified | report |
| 15 | ResNet-50 (DADA) | 77.5 | – | Paper | Code | 2020 | 5 of 9 ran · 4 unverified | report |
| 16 | ResNet-50 (Faster AA) | 76.5 | – | Paper | Code | 2019 | 0 of 9 ran · 9 unverified | report |
| 17 | DeiT-T (+MixPro) | 73.8 | – | Paper | Code | 2023 | 10 of 18 ran · 8 unverified | report |
All 17 rows shown. 17 link to a paper page on this site; 0 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). 12 rows have a graph line, from 7 distinct papers; 9 rows (5 papers) have at least one sample that ran. Counting each paper once: Syntology ran 101 of 185 samples; 84 unverified. Separately, 22 of those 185 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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