VQ-GAN: Taming Transformers for High-Resolution Image Synthesis | Paper Explained

❤️ Become The AI Epiphany Patreon ❤️ ► https://www.patreon.com/theaiepiphany In this video I cover VQ-GAN or Taming Transformers for High-Resolution Image Synthesis. It uses modified VQ-VAEs and a powerful transformer (GPT-2) to synthesize high-res images. An important modification of VQ-VAE they brought are: 1) changing MSE for perceptual loss 2) adding adversarial loss which makes the images way more crispy compared to the original VQ-VAE which had blurry outputs. ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ ✅ Paper: https://arxiv.org/abs/2012.09841 ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ ⌚️ Timetable: 00:00 Intro 01:50 A high-level VQ-GAN overview 04:00 Perceptual loss 05:10 Patch-based adversarial loss 06:45 Sequence prediction via GPT 09:50 Generating high-res images 12:45 Loss explained in depth 16:15 Training the transformer 17:50 Conditioning transformer 20:45 Comparisons and results 22:00 Sampling strategies 23:00 Comparisons and results continued 25:00 Rejection sampling with ResNet or CLIP 26:45 Receptive field effects 28:30 Comparisons with DALL-E ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 💰 BECOME A PATREON OF THE AI EPIPHANY ❤️ If these videos, GitHub projects, and blogs help you, consider helping me out by supporting me on Patreon! The AI Epiphany ► https://www.patreon.com/theaiepiphany One-time donation: https://www.paypal.com/paypalme/theaiepiphany Much love! ❤️ Huge thank you to these AI Epiphany patreons: Eli Mahler Petar Veličković Zvonimir Sabljic ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 💡 The AI Epiphany is a channel dedicated to simplifying the field of AI using creative visualizations and in general, a stronger focus on geometrical and visual intuition, rather than the algebraic and numerical "intuition". ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 👋 CONNECT WITH ME ON SOCIAL LinkedIn ► https://www.linkedin.com/in/aleksagordic/ Twitter ► https://twitter.com/gordic_aleksa Instagram ► https://www.instagram.com/aiepiphany/ Facebook ► https://www.facebook.com/aiepiphany/ 👨‍👩‍👧‍👦 JOIN OUR DISCOR