Yao Zhu

ImageNet-E: Benchmarking Neural Network Robustness via Attribute Editing

2023

Recent studies have shown that higher accuracy on ImageNet usually leads to better robustness against different corruptions. Therefore, in this paper, instead of following the traditional research paradigm that investigates new out-of-distribution corruptions or perturbations …