Image Classification on SVHN 250 labels
1.88Test Error RateCRMatch
Evaluation Results
| Method | Links | |
|---|---|---|
| CRMatch2023.11 | 1.88 | |
| SequenceMatchBackbone=Wide-ResNet-28-2, #LABEL=2502023.10 | 1.89 | |
| UDA2021.10 | 1.92 | |
| UDABackbone=Wide-ResNet-28-2, #LABEL=2502023.10 | 1.92 | |
| FixMatch2025.05 | 1.93 | |
| FreeMatchBackbone=Wide-ResNet-28-2, #LABEL=2502023.10 | 1.97 | |
| Dash2025.05 | 1.97 | |
| Dash2023.11 | 1.97 | |
| FlexMatch2025.05 | 1.98 | |
| FixMatch2023.11 | 1.99 | |
| CoMatch2025.05 | 2.01 | |
| FixMatch2021.10 | 2.02 | |
| FixMatchBackbone=Wide-ResNet-28-2, #LABEL=2502023.10 | 2.02 | |
| DASHBackbone=Wide-ResNet-28-2, #LABEL=2502023.10 | 2.04 | |
| SimMatch2025.05 | 2.13 | |
| SoftMatch2023.11 | 2.15 | |
| DP-SSLTraining Labels=2502022.05 | 2.16 | |
| CRMatch2025.05 | 2.16 | |
| MPLBackbone=Wide-ResNet-28-2, #LABEL=2502023.10 | 2.29 | |
| MPL2023.11 | 2.29 | |
| Boosted SSLlabeled samples=2502020.12 | 2.3 | |
| DoubleMatchTraining Labels=250, Evaluation Protocol=min2022.05 | 2.37 | |
| DoubleMatch2023.11 | 2.37 | |
| Dash (CTA)Training Labels=2502022.05 | 2.38 | |
| FixMatchlabeled samples=250, augmentation=RandAugment2020.12 | 2.48 | |
| SimMatchV22025.05 | 2.48 | |
| DoubleMatchTraining Labels=250, Evaluation Protocol=last 202022.05 | 2.58 | |
| FixMatchlabeled samples=250, augmentation=CTA2020.12 | 2.64 | |
| FixMatch (CTA)Training Labels=2502022.05 | 2.64 | |
| ReMixMatchlabeled samples=2502020.12 | 2.92 | |
| ReMixMatchTraining Labels=2502022.05 | 2.92 | |
| SimMatchV22023.11 | 2.92 | |
| Semi-SSTBackbone=ViT-Small, Pre-training=DINO2025.05 | 3.36 | |
| MixMatch2025.05 | 3.38 | |
| VAT2025.05 | 3.44 | |
| Mean Teacher2021.10 | 3.45 | |
| MeanTeacherBackbone=Wide-ResNet-28-2, #LABEL=2502023.10 | 3.45 | |
| Triple-GAN-V2Classifier=13-layer CNN [32], Data Augmentation=Standard2019.12 | 3.48 | |
| Mean Teacherlabeled samples=2502020.12 | 3.57 | |
| MixMatchlabeled samples=2502020.12 | 3.98 | |
| MixMatchTraining Labels=2502022.05 | 3.98 | |
| FreeMatch2023.11 | 4.09 | |
| Super-SSTBackbone=ViT-Small, Pre-training=DINO2025.05 | 4.17 | |
| SNTGClassifier=13-layer CNN (similar), Data Augmentation=Standard2019.12 | 4.29 | |
| VAT2021.10 | 4.33 | |
| VATBackbone=Wide-ResNet-28-2, #LABEL=2502023.10 | 4.33 | |
| MTClassifier=13-layer CNN (similar), Data Augmentation=Standard2019.12 | 4.35 | |
| MixMatch2021.10 | 4.56 | |
| MixMatchBackbone=Wide-ResNet-28-2, #LABEL=2502023.10 | 4.56 | |
| ReMixMatch2025.05 | 4.69 | |
| MT (our code base)Classifier=13-layer CNN [32], Data Augmentation=Standard2019.12 | 4.89 | |
| UDA2025.05 | 5.65 | |
| UDAlabeled samples=2502020.12 | 5.69 | |
| UDATraining Labels=2502022.05 | 5.69 | |
| ReMixMatch2021.10 | 6.36 | |
| ReMixMatchBackbone=Wide-ResNet-28-2, #LABEL=2502023.10 | 6.36 | |
| FlexMatch2021.10 | 6.59 | |
| FlexMatchBackbone=Wide-ResNet-28-2, #LABEL=2502023.10 | 6.59 | |
| AdaMatch2025.05 | 8.74 | |
| NP-Match2023.11 | 9.51 | |
| II modelClassifier=13-layer CNN (similar), Data Augmentation=Standard2019.12 | 9.69 | |
| Π-Model2021.10 | 13.3 | |
| Pi ModelBackbone=Wide-ResNet-28-2, #LABEL=2502023.10 | 13.3 | |
| Pseudo-Labeling2025.05 | 13.46 | |
| Pi Model2023.11 | 13.55 | |
| Pseudo-Labeling2021.10 | 15.59 | |
| Pseudo LabelBackbone=Wide-ResNet-28-2, #LABEL=2502023.10 | 15.59 | |
| Mean Teacher2025.05 | 16.47 | |
| PI-Modellabeled samples=2502020.12 | 18.96 | |
| Pseudo-Labelinglabeled samples=2502020.12 | 20.21 | |
| Pi-Model2025.05 | 24.17 | |
| MeanTeacher2023.11 | 25.1 |