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ImageNet - 1% labeled data Benchmark (Semi-Supervised Image Classification)
Semi-supervised image classification leverages unlabelled data as well as labelled data to increase classification performance.
You may want to read some blog posts to get an overview before reading the papers and checking the leaderboards:
- An overview of proxy-label approaches for semi-supervised learning - Sebastian Ruder
- Semi-Supervised Learning in Computer Vision - Amit Chaudhary
The archive carries no text for this table; the description above is the archive's text for the task Semi-Supervised Image Classification. archive 2025-07-28
Over time archive 2025-07-28
The chart needs JavaScript; the table below carries every value.
Direction inferred from the metric name, not from the archive: Top 1 Accuracy (higher is better), Top 5 Accuracy (higher is better), Number of params (lower is better). Points are placed at the row's paper date; 64 of 65 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 | DHO (ViT-Large) | 84.6% | – | Paper | Code | 2025 | linked, not harvested | report | ||
| 2 | REACT (ViT-Large) | 81.6% | ✓ | Paper | Code | 2023 | 6 of 17 ran · 11 unverified | report | ||
| 3 | DHO (ViT-Base) | 81.6% | – | Paper | Code | 2025 | linked, not harvested | report | ||
| 4 | Meta Co-Training | 80.7% | – | Paper | Code | 2023 | 1 of 1 ran · 0 unverified | report | ||
| 5 | Semi-SST (ViT-Huge) | 80.7% | – | Paper | – | 2025 | no code linked | report | ||
| 6 | Super-SST (ViT-Huge) | 80.3% | – | Paper | – | 2025 | no code linked | report | ||
| 7 | Semi-ViT (ViT-Huge) | 80% | 93.1 | – | Paper | Code | 2022 | linked, not harvested | report | |
| 8 | Semi-ViT (ViT-Large) | 77.3% | – | Paper | Code | 2022 | linked, not harvested | report | ||
| 9 | Super-SST (ViT-Small distilled) | 76.9% | – | Paper | – | 2025 | no code linked | report | ||
| 10 | SimCLRv2 self-distilled (ResNet-152 x3, SK) | 76.6% | 93.4% | – | Paper | Code | 2020 | 0 of 6 ran · 6 unverified | report | |
| 11 | SimCLRv2 distilled (ResNet-50 x2, SK) | 75.9% | 93.0% | – | Paper | Code | 2020 | 0 of 6 ran · 6 unverified | report | |
| 12 | MSN (ViT-B/4) | 75.7% | – | Paper | Code | 2022 | 4 of 4 ran · 0 unverified | report | ||
| 13 | SimCLRv2 (ResNet-152 x3, SK) | 74.9% | 92.3% | – | Paper | Code | 2020 | 0 of 6 ran · 6 unverified | report | |
| 14 | SimCLRv2 distilled (ResNet-50) | 73.9% | 91.5% | – | Paper | Code | 2020 | 0 of 6 ran · 6 unverified | report | |
| 15 | SimMatchV2 (ResNet-50) | 71.9% | – | Paper | Code | 2023 | linked, not harvested | report | ||
| 16 | Semi-SST (ViT-Small) | 71.4% | – | Paper | – | 2025 | no code linked | report | ||
| 17 | DebiasPL (ResNet-50) | 71.3% | – | Paper | Code | 2022 | 1 of 1 ran · 0 unverified | report | ||
| 18 | BYOL (ResNet-200 x2) | 71.2% | 89.5% | – | Paper | Code | 2020 | 62 of 79 ran · 17 unverified | report | |
| 19 | Semi-ViT (ViT-Base) | 71% | – | Paper | Code | 2022 | linked, not harvested | report | ||
| 20 | Super-SST (ViT-Small) | 70.4% | – | Paper | – | 2025 | no code linked | report | ||
| 21 | PAWS (ResNet-50 4x) | 69.9% | – | Paper | Code | 2021 | 7 of 21 ran · 14 unverified | report | ||
| 22 | PAWS (ResNet-50 2x) | 69.6% | – | Paper | Code | 2021 | 7 of 21 ran · 14 unverified | report | ||
| 23 | BYOL (ResNet-50 x4) | 69.1% | 87.9% | – | Paper | Code | 2020 | 62 of 79 ran · 17 unverified | report | |
| 24 | SimMatch + EPASS (ResNet-50) | 68.6% | 87.6 | – | Paper | Code | 2023 | linked, not harvested | report | |
| 25 | CoMatch + EPASS (ResNet-50) | 67.4% | 87.3 | – | Paper | Code | 2023 | linked, not harvested | report | |
| 26 | TWIST (ResNet-50 x2) | 67.2% | 88.2% | – | Paper | Code | 2021 | 5 of 15 ran · 10 unverified | report | |
| 27 | SimMatch (ResNet-50) | 67.2% | – | Paper | Code | 2022 | linked, not harvested | report | ||
| 28 | CoMatch (w. MoCo v2) | 67.1% | 87.1% | – | Paper | Code | 2020 | 2 of 3 ran · 1 unverified | report | |
| 29 | PAWS (ResNet-50) | 66.5% | – | Paper | Code | 2021 | 7 of 21 ran · 14 unverified | report | ||
| 30 | SimCLRv2 (ResNet-50 ×2) | 66.3% | 87.4% | – | Paper | Code | 2020 | 0 of 6 ran · 6 unverified | report | |
| 31 | WCL (ResNet-50) | 65.0% | 86.3% | – | Paper | Code | 2021 | 0 of 3 ran · 3 unverified | report | |
| 32 | FNC (ResNet-50) | 63.7% | 85.3% | – | Paper | Code | 2020 | linked, not harvested | report | |
| 33 | SimCLR (ResNet-50 4×) | 63.0% | 85.8% | – | Paper | Code | 2020 | 79 of 137 ran · 58 unverified | report | |
| 34 | FixMatch-EMAN | 63% | – | Paper | Code | 2021 | linked, not harvested | report | ||
| 35 | SEER (RegNet10B) | 62.4% | – | Paper | Code | 2022 | linked, not harvested | report | ||
| 36 | BYOL (ResNet-50 x2) | 62.2% | 84.1% | – | Paper | Code | 2020 | 62 of 79 ran · 17 unverified | report | |
| 37 | iBOT (ViT-S/16) | 61.9% | – | Paper | Code | 2021 | 0 of 1 ran · 1 unverified | report | ||
| 38 | SEER Large (RegNetY-256GF) | 60.5% | – | Paper | Code | 2021 | linked, not harvested | report | ||
| 39 | SemiReward | 59.64% | – | Paper | Code | 2023 | 4 of 5 ran · 1 unverified | report | ||
| 40 | SimCLR (ResNet-50 2×) | 58.5% | 83.0% | – | Paper | Code | 2020 | 79 of 137 ran · 58 unverified | report | |
| 41 | RELICv2 | 58.1% | 81.3 | – | Paper | Code | 2022 | 0 of 14 ran · 14 unverified | report | |
| 42 | SimCLRv2 (ResNet-50) | 57.9% | 82.5% | – | Paper | Code | 2020 | 0 of 6 ran · 6 unverified | report | |
| 43 | SEER Small (RegNetY-128GF) | 57.5% | – | Paper | Code | 2021 | linked, not harvested | report | ||
| 44 | NNCLR (ResNet-50) | 56.4% | 80.7 | – | Paper | Code | 2021 | 4 of 5 ran · 1 unverified | report | |
| 45 | I-VNE+ (ResNet-50) | 55.8 | 81.0 | – | Paper | Code | 2023 | linked, not harvested | report | |
| 46 | Barlow Twins (ResNet-50) | 55% | 79.2 | – | Paper | Code | 2021 | 21 of 26 ran · 5 unverified | report | |
| 47 | VICREG (Resnet-50) | 54.8% | 79.4% | – | Paper | Code | 2021 | 11 of 17 ran · 6 unverified | report | |
| 48 | SwAV (ResNet-50) | 53.9% | 78.5 | – | Paper | Code | 2020 | 13 of 17 ran · 4 unverified | report | |
| 49 | BYOL (ResNet-50) | 53.2% | 78.4% | – | Paper | Code | 2020 | 62 of 79 ran · 17 unverified | report | |
| 50 | CPC v2 (ResNet-161) | 52.7% | 77.9% | – | – | – | not matched | report | ||
| 51 | SynCo (ResNet-50) 800ep | 50.8% | 77.5% | 24M | – | Paper | Code | 2024 | linked, not harvested | report |
| 52 | SimCLR (ResNet-50) | 48.3% | 75.5% | – | Paper | Code | 2020 | 79 of 137 ran · 58 unverified | report | |
| 53 | SCAN (ResNet-50|Unsupervised) | 39.90% | 60.0% | – | Paper | Code | 2020 | linked, not harvested | report | |
| 54 | OBoW (ResNet-50) | 82.9% | – | Paper | Code | 2020 | 3 of 3 ran · 0 unverified | report | ||
| 55 | PCL (ResNet-50) | 75.6% | – | Paper | Code | 2020 | 2 of 5 ran · 3 unverified | report | ||
| 56 | CPC | 64.03% | – | Paper | Code | 2018 | 29 of 45 ran · 16 unverified | report | ||
| 57 | BigBiGAN (RevNet-50 ×4, BN+CReLU) | 55.2% | – | Paper | Code | 2019 | 0 of 3 ran · 3 unverified | report | ||
| 58 | Rotation (joint training) | 53.37% | – | Paper | Code | 2019 | 0 of 19 ran · 19 unverified | report | ||
| 59 | Pseudolabeling | 51.56% | – | Paper | Code | 2019 | 0 of 19 ran · 19 unverified | report | ||
| 60 | Exemplar (joint training) | 47.02% | – | Paper | Code | 2019 | 0 of 19 ran · 19 unverified | report | ||
| 61 | VAT + Entropy Minimization | 46.96% | – | Paper | Code | 2019 | 0 of 19 ran · 19 unverified | report | ||
| 62 | Rotation | 45.11% | – | Paper | Code | 2019 | 0 of 19 ran · 19 unverified | report | ||
| 63 | Exemplar | 44.90% | – | Paper | Code | 2019 | 0 of 19 ran · 19 unverified | report | ||
| 64 | VAT | 44.05% | – | Paper | Code | 2019 | 0 of 19 ran · 19 unverified | report | ||
| 65 | Instance Discrimination (ResNet-50) | 39.20% | – | Paper | Code | 2018 | linked, not harvested | report |
All 65 rows shown. 64 link to a paper page on this site; 1 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). 41 rows have a graph line, from 23 distinct papers; 24 rows (17 papers) have at least one sample that ran. Counting each paper once: Syntology ran 254 of 447 samples; 193 unverified. Separately, 168 of those 447 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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