Venue: ICML 2021 Workshop AML

Reviews:

final_score: rating: Accept
review_content: This paper proposes the meta adversarial training (MAT) method, which meta learns an initialization and uses I-FGSM to craft adversarial patches during training. This strategy is more efficient compared to previous methods and is empirically verified on different datasets. MAT can effectively defend against physical attacks and is worthy of more attention from the community.
review_title: Interesting work

Meta-review: This paper proposes MAT for training robust models against patch attacks. The effectiveness is verified on different datasets.
Decision: Accept (Poster)