latent diffusion models

The Latent Diffusion Model (LDM) is a diffusion model architecture developed developed by the CompVis (Computer Vision & Learning) group at LMU Munich. Introduced in 2015, diffusion models (DM) are trained with the objective of removing successive applications of Gaussian noise on training images. The LDM is an improvement on standard DM by performing diffusion modeling in latent space, and by allowing self-attention and cross-attention conditioning. LDM are widely used in practical diffusion models. The Stable Diffusion 1.1 up to SD 2.1 were based on the LDM architecture.