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In the paper, the authors introduce a new unsupervised deep learning method — Invariant Information Clustering (IIC).[1] IIC directly trains a randomly initialized neural network into a classification function, end-to-end and without any labels. It involves a simple objective function, which is the mutual information between the function’s classifications for paired data samples.

IIC can be applied to image clustering as well as image segmentation. In this project, we reproduce the segmentation part. In the image segmentation process, we do some transformations(e.g. flipping, colorjitting) to each image and add displacements to each pixel.

Prepare data

In the reproduction project, we use Potsdam…

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