@article{latentdiffusionstablediffusion2022,
  title = {High-Resolution Image Synthesis with Latent Diffusion Models},
  author = {Rombach, R. and Blattmann, A. and Lorenz, D. and Esser, P. and Ommer, B.},
  year = {2022},
  journal = {CVPR 2022 (IEEE/CVF)},
  url = {https://arxiv.org/abs/2112.10752},
  abstract = {This paper introduces latent diffusion models (LDMs), which perform the iterative denoising process in a learned latent space rather than pixel space, making high-resolution image synthesis computationally tractable. The architecture became the technical foundation of Stable Diffusion and its derivatives, the dominant open-source image-generation systems now embedded in animation pre-production workflows including concept art, storyboarding, and moodboarding. For animation educators, this is the primary text behind the class of generative tools most likely to appear in student and studio practice.},
  keywords = {generative-ai, image-generation, training-data, curriculum-design},
  note = {AI \& Animation Education Knowledge Base}
}