290141d6bfd7ea4d3f4483d126609bf6-Supplemental-Conference.pdf

The input toeach projection head is the output of the backbone network - a feature vector of size512 and the output dimension is the number of style dimensions - in the case of the pretrained CLEVR styleGAN2 used in our experiments,thisvalueis204. For the generator, we use a modified version of styleGAN2 that is trained to output images of resolution 128 128. For each input image of sizeH W C, we start by generating a random mask of sizeH W where each pixel value in contained in the interval[0,1]. These thresholds were obtained by visual inspection. In this experiment, we set out to measure the variability of the predicted quantile intervals as a functionofproblemdifficulty.