ImageNet-C

Introduced by Hendrycks et al. in Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

ImageNet-C is an open source data set that consists of algorithmically generated corruptions (blur, noise) applied to the ImageNet test-set.

Source: Selective Brain Damage: Measuring the Disparate Impact of Model Pruning

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Task	Dataset Variant	Best Model
Domain Generalization	ImageNet-C	DINOv2
Unsupervised Domain Adaptation	ImageNet-C	EfficientNet-L2+RPL
Adversarial Robustness	ImageNet-C	DeiT-S

Paper	Code	Results	Date	Stars

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ImageNet-R

Source: https://arxiv.org/pdf/1807.01697.pdf.