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Robustness of SAM: Segment Anything under corruptions and beyond
This work investigates the robustness of SAM to corruptions and adversarial attacks. -
Benchmarking neural network robustness to common corruptions and perturbations
Benchmarking neural network robustness to common corruptions and perturbations. -
ImageNet-C
The dataset used in the paper is the ImageNet-C dataset, which is a dataset of images corrupted with various types of noise and occlusions.