| 1 | EfficientNet-L2+RPL | 22 | Yes | If your data distribution shifts, use self-learn... | 2021-04-27 | Code |
| 2 | EfficientNet-L2+ENT | 23 | Yes | If your data distribution shifts, use self-learn... | 2021-04-27 | Code |
| 3 | DINOv2 (ViT-g/14, frozen model, linear eval) | 28.2 | Yes | DINOv2: Learning Robust Visual Features without ... | 2023-04-14 | Code |
| 4 | CAFormer-B36 (IN21K, 384) | 30.8 | Yes | MetaFormer Baselines for Vision | 2022-10-24 | Code |
| 5 | MAE+DAT (ViT-H) | 31.4 | No | Enhance the Visual Representation via Discrete A... | 2022-09-16 | Code |
| 6 | DINOv2 (ViT-L/14, frozen model, linear eval) | 31.5 | Yes | DINOv2: Learning Robust Visual Features without ... | 2023-04-14 | Code |
| 7 | CAFormer-B36 (IN21K) | 31.8 | Yes | MetaFormer Baselines for Vision | 2022-10-24 | Code |
| 8 | MAE (ViT-H) | 33.8 | No | Masked Autoencoders Are Scalable Vision Learners | 2021-11-11 | Code |
| 9 | ResNeXt101 32x8d + DeepAug + Augmix + RPL | 34.8 | No | If your data distribution shifts, use self-learn... | 2021-04-27 | Code |
| 10 | ConvFormer-B36 (IN21K) | 35 | Yes | MetaFormer Baselines for Vision | 2022-10-24 | Code |
| 11 | ResNeXt101 32x8d + DeepAug + Augmix + ENT | 35.5 | No | If your data distribution shifts, use self-learn... | 2021-04-27 | Code |
| 12 | FAN-L-Hybrid (IN-22k) | 35.8 | Yes | Understanding The Robustness in Vision Transform... | 2022-04-26 | Code |
| 13 | Pyramid Adversarial Training Improves ViT (Im21k) | 36.8 | Yes | Pyramid Adversarial Training Improves ViT Perfor... | 2021-11-30 | Code |
| 14 | ResNeXt101+DeepAug+AugMix, BatchNorm Adaptation, full adaptation | 38 | No | Improving robustness against common corruptions ... | 2020-06-30 | Code |
| 15 | VOLO-D5+HAT | 38.4 | No | Improving Vision Transformers by Revisiting High... | 2022-04-03 | Code |
| 16 | DiscreteViT (Im21k) | 38.74 | Yes | Discrete Representations Strengthen Vision Trans... | 2021-11-20 | Code |
| 17 | ConvNeXt-XL (Im21k) (augmentation overlap with ImageNet-C) | 38.8 | Yes | A ConvNet for the 2020s | 2022-01-10 | Code |
| 18 | GPaCo (ViT-L) | 39 | No | Generalized Parametric Contrastive Learning | 2022-09-26 | Code |
| 19 | ResNeXt101+DeepAug+AugMix, BatchNorm Adaptation, 8 samples | 40.7 | No | Improving robustness against common corruptions ... | 2020-06-30 | Code |
| 20 | ResNeXt101 32x8d + IG-3.5B + ENT | 40.8 | Yes | If your data distribution shifts, use self-learn... | 2021-04-27 | Code |
| 21 | ResNeXt101 32x8d + IG-3.5B + RPL | 40.9 | Yes | If your data distribution shifts, use self-learn... | 2021-04-27 | Code |
| 22 | FAN-B-Hybrid (IN-22k) | 41 | Yes | Understanding The Robustness in Vision Transform... | 2022-04-26 | Code |
| 23 | Pyramid Adversarial Training Improves ViT | 41.42 | No | Pyramid Adversarial Training Improves ViT Perfor... | 2021-11-30 | Code |
| 24 | FAN-L-Hybrid+STL | 42.1 | No | Fully Attentional Networks with Self-emerging To... | 2024-01-08 | Code |
| 25 | QualNet (ResNeXt101) | 42.5 | No | - | - | Code |
| 26 | CAFormer-B36 | 42.6 | No | MetaFormer Baselines for Vision | 2022-10-24 | Code |
| 27 | DINOv2 (ViT-B/14, frozen model, linear eval) | 42.7 | Yes | DINOv2: Learning Robust Visual Features without ... | 2023-04-14 | Code |
| 28 | FAN-L-Hybrid | 43 | No | Understanding The Robustness in Vision Transform... | 2022-04-26 | Code |
| 29 | ResNeXt101 32x8d + RPL | 43.2 | No | If your data distribution shifts, use self-learn... | 2021-04-27 | Code |
| 30 | ResNeXt101 32x8d + ENT | 44.3 | No | If your data distribution shifts, use self-learn... | 2021-04-27 | Code |
| 31 | ResNet50+DeepAug+AugMix, BatchNorm Adaptation, full adaptation | 45.4 | No | Improving robustness against common corruptions ... | 2020-06-30 | Code |
| 32 | DrViT | 46.22 | No | Discrete Representations Strengthen Vision Trans... | 2021-11-20 | Code |
| 33 | DiscreteViT | 46.22 | No | Discrete Representations Strengthen Vision Trans... | 2021-11-20 | Code |
| 34 | ConvFormer-B36 | 46.3 | No | MetaFormer Baselines for Vision | 2022-10-24 | Code |
| 35 | RVT-B* | 46.8 | No | Towards Robust Vision Transformer | 2021-05-17 | Code |
| 36 | ResNet50+DeepAug+AugMix, BatchNorm Adaptation, 8 samples | 48.4 | No | Improving robustness against common corruptions ... | 2020-06-30 | Code |
| 37 | Sequencer2D-L | 48.9 | No | Sequencer: Deep LSTM for Image Classification | 2022-05-04 | Code |
| 38 | RVT-S* | 49.4 | No | Towards Robust Vision Transformer | 2021-05-17 | Code |
| 39 | ResNet-50 (PushPull-Conv) + PRIME | 49.95 | No | PushPull-Net: Inhibition-driven ResNet robust to... | 2024-08-07 | Code |
| 40 | ResNet50 + RPL | 50.5 | No | If your data distribution shifts, use self-learn... | 2021-04-27 | Code |
| 41 | QualNet (ResNet-50) | 50.6 | No | - | - | Code |
| 42 | PRIME + DeepAugment (ResNet-50) | 51.3 | No | PRIME: A few primitives can boost robustness to ... | 2021-12-27 | Code |
| 43 | ResNet50 + ENT | 51.6 | No | If your data distribution shifts, use self-learn... | 2021-04-27 | Code |
| 44 | GFNet-S | 53.8 | No | Global Filter Networks for Image Classification | 2021-07-01 | Code |
| 45 | DINOv2 (ViT-S/14, frozen model, linear eval) | 54.4 | Yes | DINOv2: Learning Robust Visual Features without ... | 2023-04-14 | Code |
| 46 | PRIME with JSD (ResNet-50) | 55.5 | No | PRIME: A few primitives can boost robustness to ... | 2021-12-27 | Code |
| 47 | RVT-Ti* | 57 | No | Towards Robust Vision Transformer | 2021-05-17 | Code |
| 48 | PRIME (ResNet-50) | 57.5 | No | PRIME: A few primitives can boost robustness to ... | 2021-12-27 | Code |
| 49 | APR-SP + DeepAugment (ResNet-50) | 57.5 | No | Amplitude-Phase Recombination: Rethinking Robust... | 2021-08-19 | Code |
| 50 | DeepAugment (ResNet-50) | 60.4 | No | The Many Faces of Robustness: A Critical Analysi... | 2020-06-29 | Code |
| 51 | ResNet50 (baseline), BatchNorm Adaptation, full adaptation | 62.2 | No | Improving robustness against common corruptions ... | 2020-06-30 | Code |
| 52 | ResNet50 (baseline), BatchNorm Adaptation, 8 samples | 65 | No | Improving robustness against common corruptions ... | 2020-06-30 | Code |
| 53 | APR-SP (ResNet-50) | 65 | No | Amplitude-Phase Recombination: Rethinking Robust... | 2021-08-19 | Code |
| 54 | AugMix (ResNet-50) | 65.3 | No | AugMix: A Simple Data Processing Method to Impro... | 2019-12-05 | Code |
| 55 | Stylized ImageNet (ResNet-50) | 69.3 | Yes | ImageNet-trained CNNs are biased towards texture... | 2018-11-29 | Code |
| 56 | Group-wise Inhibition (ResNet-50) | 69.6 | No | Group-wise Inhibition based Feature Regularizati... | 2021-03-03 | Code |
| 57 | ResNet-50 | 76.7 | No | Benchmarking Neural Network Robustness to Common... | 2019-03-28 | Code |