The shape and simplicity biases of adversarially robust ImageNet-trained
CNNs
Papers citing "The shape and simplicity biases of adversarially robust ImageNet-trained CNNs"
13 / 13 papers shown
Title |
|---|
 DiG-IN: Diffusion Guidance for Investigating Networks -- Uncovering
Classifier Differences Neuron Visualisations and Visual Counterfactual
ExplanationsComputer Vision and Pattern Recognition (CVPR), 2023 |
 ImageNet-Hard: The Hardest Images Remaining from a Study of the Power of
Zoom and Spatial Biases in Image ClassificationNeural Information Processing Systems (NeurIPS), 2023 |
 Partial success in closing the gap between human and machine visionNeural Information Processing Systems (NeurIPS), 2021 |
 Inverting Adversarially Robust Networks for Image SynthesisAsian Conference on Computer Vision (ACCV), 2021 |
 Do Input Gradients Highlight Discriminative Features?Neural Information Processing Systems (NeurIPS), 2021 |
