[D]Use SimCLR as pretraining for image segmentation

This page summarizes the projects mentioned and recommended in the original post on /r/MachineLearning

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  • contrastive-reconstruction

    Tensorflow-keras implementation for Contrastive Reconstruction (ConRec) : a self-supervised learning algorithm that obtains image representations by jointly optimizing a contrastive and a self-reconstruction loss.

  • How about this: https://github.com/bayer-science-for-a-better-life/contrastive-reconstruction

  • self_supervised

    Implementation of popular SOTA self-supervised learning algorithms as Fastai Callbacks.

  • You may want to check out pip install self-supervised https://github.com/KeremTurgutlu/self_supervised which benchmarks several selfsupervised methods, here's a SimCLR tutorial https://keremturgutlu.github.io/self_supervised/01%20-%20training_simclr_iwang.html

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  • solo-learn

    solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning

  • vissl

    Discontinued VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.

  • I recently did some self supervised pretrainings (simclr, moco, Barlow twins) and used the vissl library for that which has worked pretty well for me (https://github.com/facebookresearch/vissl)

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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