Question About Discriminator of CycleGan

Question

Question About Discriminator of CycleGan

Melon Eusk

2022年5月26日 04:09

The Discriminator of CycleGan outputs not just a single value to say that the image is real or fake.... But It outputs a grid of numbers (like 8X8 or 7x7), where each number says whether one patch of the input image is fake or real.

So, my question is that, why do we do this.. What benefits does it gives us, and what was the problem in the approach where we only outputted a single value?

Topic cyclegan gan deep-learning neural-network machine-learning

Category Data Science

noe · Accepted Answer · 2021年3月21日 16:08

This is explained in the original CycleGAN paper:

For the discriminator networks we use 70 × 70 PatchGANs, which aim to classify whether 70 × 70 overlapping image patches are real or fake. Such a patch-level discriminator architecture has fewer parameters than a full-image discriminator and can work on arbitrarily sized images in a fully convolutional fashion.

Therefore, the arguments for using patch-based discriminators are that:

It has fewer parameters.
It enables using them in arbitrarily sized images.