Awesome - Image Classification

A curated list of deep learning image classification papers and codes since 2014, Inspired by awesome-object-detection, deep_learning_object_detection and awesome-deep-learning-papers.

Background

I believe image classification is a great start point before diving into other computer vision fields, espacially for begginers who know nothing about deep learning. When I started to learn computer vision, I've made a lot of mistakes, I wish someone could have told me that which paper I should start with back then. There doesn't seem to have a repository to have a list of image classification papers like deep_learning_object_detection until now. Therefore, I decided to make a repository of a list of deep learning image classification papers and codes to help others. My personal advice for people who know nothing about deep learning, try to start with vgg, then googlenet, resnet, feel free to continue reading other listed papers or switch to other fields after you are finished.

Note: I also have a repository of pytorch implementation of some of the image classification networks, you can check out here.

Performance Table

For simplicity reason, I only listed the best top1 and top5 accuracy on ImageNet from the papers. Note that this does not necessarily mean one network is better than another when the acc is higher, cause some networks are focused on reducing the model complexity instead of improving accuracy, or some papers only give the single crop results on ImageNet, but others give the model fusion or multicrop results.

• ConvNet: name of the covolution network
• ImageNet top1 acc: best top1 accuracy on ImageNet from the Paper
• ImageNet top5 acc: best top5 accuracy on ImageNet from the Paper
• Published In: which conference or journal the paper was published in.

ConvNet	ImageNet top1 acc	ImageNet top5 acc	Published In