What is adversarial training in computer vision and why is it important?

Adversarial training improves model robustness by training on adversarially perturbed inputs.

Adversarial training generates small perturbations in input images that are designed to fool the model. The model is then trained on both clean and adversarial examples, improving robustness against attacks and distribution shifts. This is crucial in safety-critical applications like autonomous driving.