Reviews: A Simple Cache Model for Image Recognition

This paper presents a cache model to be used in image recognition tasks. The authors argue that class specific information can be retrieved from earlier layers of the network to improve the accuracy of an already trained model, without having to re-train of finetune. This is achieved by extracting and caching the activations of some layers along with the class at training time. At test time a similarity measure is used to calculate how far/close the input is compared to information stored in memory. Experiments show that performance is improved in CIFAR 10/100 and ImageNet.