Loss of contrast when training GANs

username: import-antigravity
cooked: <p>I’m working on a research project using GANs and I’m trying to get a baseline by training a basic DCGAN on the CelebA dataset. I know we’re spoiled by StyleGAN and BigGAN, but without any esoteric optimizations the results are already looking decent by the 7th epoch or so:</p>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/b/c/bc6c06bad5ada1f0e669f9d47744a387f53e6019.png" data-download-href="https://discuss.pytorch.org/uploads/default/bc6c06bad5ada1f0e669f9d47744a387f53e6019" title="Screen Shot 2021-07-28 at 10.28.11 AM"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/b/c/bc6c06bad5ada1f0e669f9d47744a387f53e6019_2_443x500.png" alt="Screen Shot 2021-07-28 at 10.28.11 AM" data-base62-sha1="qSRd05lkLv5Rb8Hdi0o6ci41ShH" width="443" height="500" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/b/c/bc6c06bad5ada1f0e669f9d47744a387f53e6019_2_443x500.png, https://discuss.pytorch.org/uploads/default/optimized/3X/b/c/bc6c06bad5ada1f0e669f9d47744a387f53e6019_2_664x750.png 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/b/c/bc6c06bad5ada1f0e669f9d47744a387f53e6019.png 2x" data-dominant-color="8B7E77"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">Screen Shot 2021-07-28 at 10.28.11 AM</span><span class="informations">756×852 281 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p>
<p>However, as training goes on the image diversity and fidelity improves but the image contrast decreases substantially:</p>
<p><div class="lightbox-wrapper"><a class="lightbox" href="https://discuss.pytorch.org/uploads/default/original/3X/5/c/5c0e0021558f1a2b1cd055cfa6648cb2adac02c8.png" data-download-href="https://discuss.pytorch.org/uploads/default/5c0e0021558f1a2b1cd055cfa6648cb2adac02c8" title="Screen Shot 2021-07-28 at 10.27.20 AM"><img src="https://discuss.pytorch.org/uploads/default/optimized/3X/5/c/5c0e0021558f1a2b1cd055cfa6648cb2adac02c8_2_439x500.png" alt="Screen Shot 2021-07-28 at 10.27.20 AM" data-base62-sha1="d8lVeUd4Uq2vEZrgTRiASE54HXy" width="439" height="500" srcset="https://discuss.pytorch.org/uploads/default/optimized/3X/5/c/5c0e0021558f1a2b1cd055cfa6648cb2adac02c8_2_439x500.png, https://discuss.pytorch.org/uploads/default/optimized/3X/5/c/5c0e0021558f1a2b1cd055cfa6648cb2adac02c8_2_658x750.png 1.5x, https://discuss.pytorch.org/uploads/default/original/3X/5/c/5c0e0021558f1a2b1cd055cfa6648cb2adac02c8.png 2x" data-dominant-color="8F847F"><div class="meta"><svg class="fa d-icon d-icon-far-image svg-icon" aria-hidden="true"><use href="#far-image"></use></svg><span class="filename">Screen Shot 2021-07-28 at 10.27.20 AM</span><span class="informations">758×862 279 KB</span><svg class="fa d-icon d-icon-discourse-expand svg-icon" aria-hidden="true"><use href="#discourse-expand"></use></svg></div></a></div></p>
<p>This is a very strange pathology because you would expect the discriminator to pick up on something like this and immediately exploit it. Any ideas?</p>