Critical Flaw in VAE for Stable Diffusion: Smuggling Global Image Info through a Few Pixels
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The author of a HackerNews post highlights a critical flaw in the VAE (Variational Autoencoder) used in Stable Diffusion 1.x/2.x and other models. The flaw is likely due to bad training and results in a latent space with a high KL divergence, allowing global information about the image to be smuggled through a few pixels. The author suggests fixing the VAE without altering the latent space too much and exploring other model architectures for better performance. Comments discuss alternative models, debunking claims, and the challenges of working with neural networks.
🔗 / the_vae_used_for_stable_diffusion_1x2x_and...
#AI #Diffusion #AI
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