A ImageNet Texture

See Figures 7 and 8 for examples of the ImageNet-Texture dataset and their counterparts in the original ImageNet dataset. Shape is often less well-defined in these classes, for example in window screen and rapeseed. B.1 Comparison of two ways to apply α in NCE loss Since the denominator normalizes the 3 kinds of pairs equally, we only pay attention to the numerator. Because of the exponential tail, it applies a exponentially larger weight to the negatives that are harder. Our patch-based augmentation is also closely related to some of the self-supervised learning methods which solve jigsaw as the pretext task. All of our models are trained on 4 GTX 1080 Ti gpus.