Abstract: The explosion of image data on the Internet has the potential to foster more sophisticated and robust models and algorithms to index, retrieve, organize and interact with images and ...

Classification performance based on ImageNet is the de-facto standard metric for CNN development. In this work we challenge the notion that CNN architecture design solely based on ImageNet leads to ...

Abstract: We present a simple self-training method that achieves 88.4% top-1 accuracy on ImageNet, which is 2.0% better than the state-of-the-art model that requires 3.5B weakly labeled Instagram ...

Urban-ImageNet presents a large-scale multi-modal dataset and evaluation benchmark for urban space perception from social media imagery, organized under a hierarchical taxonomy for scene ...

This repository contains information and code on how to create Stylized-ImageNet, a stylized version of ImageNet that can be used to induce a shape bias in CNNs as reported in our paper ...

ImageNet Large Scale Visual Recognition Challenge ... Olga Russakovsky , Jia Deng , Hao Su , ...