Color augmentation is ColorJitter with {brightness, contrast, saturation, hue} strength of {0.4, 0.4, 0.4, 0.1} with an applying probability of 0.8, and RandomGrayscale with an applying probability of 0.2. Blurring augmentation [8] has a Gaussian kernel with std in [0.1, 2.0].
They didn't say the probability of gaussian blur. It's just doesn't make sense to have gaussian blur on both augmentations. Because in training the model only sees blurred images, but in testing, the blury effect is removed. This will definetely hurt the generalization ability of this model. I will use the default gaussian blur probability in simclr instead!
They didn't say the probability of gaussian blur. It's just doesn't make sense to have gaussian blur on both augmentations. Because in training the model only sees blurred images, but in testing, the blury effect is removed. This will definetely hurt the generalization ability of this model. I will use the default gaussian blur probability in simclr instead!