Adversarial Filters of Dataset Biases
Table 5: Top-1 accuracy on ImageNet-A (Hendrycks et al., 2019), an adversarial test set for image classification. The strongest model, EfficientNet-B7 improves by 2% on out-of-distribution ImageNet-A images when trained on AFLite-filtered data.
['Model', 'ImageNet-A EfficientNet-B5', 'ImageNet-A EfficientNet-B7']
As shown, all EfficientNet models struggle on this task, even when trained on the entire ImageNet. However, we find that training on AFLite-filtered data leads to models with greater generalization, in comparison to training on a randomly sampled ImageNet of the same size, leading to up to 2% improvement in performance.