2019
Retrieval-Augmented Convolutional Neural Networks Against Adversarial Examples
CVPR 2019poster
We propose a retrieval-augmented convolutional network (RaCNN) and propose to train it with local mixup, a novel variant of the recently proposed mixup algorithm. The proposed hybrid architecture combining a convolutional network and an off-the-shelf retrieval engine was designed to mitigate the adv…