A pytorch reimplement of paper "Momentum Contrast for Unsupervised Visual Representation Learning"
Shuffle BN can be applied although there is only one gpu.
we randomly select an image (in the first row), and then find the most similar/dissimilar images with the largest/smallest dot product (in the second row and third row).
As seen, with unsupervised learning, the model can capture the similarity between images.
