GinnyWeasley:

For the generator, why do we have both downsampling (Conv2d) and upsampling (ConvTranpose2d) layers? I generally know it like this for the generator that the generator only uses ConvTranpose2d layers, where the input is noise sampled from a uniform or Gaussian distribution…


Based on Section7.1 from the paper the authors are reusing the image transformation network from Perceptual Losses for Real-Time Style Transfer and Super-Resolution 4, which uses this bottleneck architecture. I can’t find more details about this choice so I would assume that this model architecture worked fine for their implementation.