Thanks for your feedback! Actually when I wrote the article, I feared this may confuse the reader. The reason why VQGAN (taming transformers) has good quality

Thanks for your feedback! Actually when I wrote the article, I feared this may confuse the reader. The reason why VQGAN (taming transformers) has good quality (possibly the best as you said) is precisely because it uses an idea from GAN (not because of quantized VAE). So, this model is not really VAE, but it's a combination of VAE and GAN just like DC-VAE model that was also featured in the post. If you take a look at VQGAN's section, you can see a comparison between DALL-E and VQGAN, the former of which uses substantially more resources and no GAN technique. THe latter shows much better quality, which shows that GAN really offers much better quality.