jlo2020/iic repository overview

⁠Invariant Information Clustering for Unsupervised Image Classification and Segmentation

This repository contains PyTorch code for the IIC paper⁠.

IIC is an unsupervised clustering objective that trains neural networks into image classifiers and segmenters without labels, with state-of-the-art semantic accuracy.

We set 9 new state-of-the-art records on unsupervised STL10 (unsupervised variant of ImageNet), CIFAR10, CIFAR20, MNIST, COCO-Stuff-3, COCO-Stuff, Potsdam-3, Potsdam, and supervised/semisupervised STL. For example:

Commands used to train the models in the paper here⁠. There you can also find the flag to turn on prediction drawing for MNIST:

How to download all our trained models including plots here⁠.

How to set up the segmentation datasets here⁠.

⁠Citation

@inproceedings{ji2019invariant,
    title={Invariant information clustering for unsupervised image classification and segmentation},
    author={Ji, Xu and Henriques, Jo{\~a}o F and Vedaldi, Andrea},
    booktitle={Proceedings of the IEEE International Conference on Computer Vision},
    pages={9865--9874},
    year={2019}
}

⁠Package dependencies

Listed here⁠. You may want to use e.g. virtualenv to isolate the environment. It's an easy way to install package versions specific to the repository that won' t affect the rest of the system.

⁠Running on your own dataset

You can either plug our loss (paper fig. 4, here⁠ and here⁠) into your own code, or change scripts in this codebase. Auxiliary overclustering makes a large difference (paper table 2) and is easy to implement, so it's strongly recommend even if you are using your own code; the others settings are less important.

New: single function to create the dataloaders for clustering here⁠.

Old thread here⁠.

⁠Forks

There are various forks of the main repository. In general I have not verified the code or performance, but check them out as someone may be working with versions of interest to you. For example:

• https://github.com/astirn/IIC⁠ (Tensorflow)
• https://github.com/nathanin/IIC⁠ (Tensorflow)
• https://github.com/sebastiani/IIC⁠ (Python 3, Pytorch 1.0)