Align Your Latents: High-Resolution Video Synthesis with Latent Diffusion Models
LMU Klinikum · Ludwig-Maximilians-Universität München · +3 more institutions
Abstract
Latent Diffusion Models (LDMs) enable high-quality image synthesis while avoiding excessive compute demands by training a diffusion model in a compressed lower-dimensional latent space. Here, we apply the LDM paradigm to high-resolution video generation, a particularly resource-intensive task. We first pre-train an LDM on images only; then, we turn the image generator into a video generator by introducing a temporal dimension to the latent space diffusion model and finetuning on encoded image sequences, i.e., videos. Similarly, we temporally align diffusion model upsamplers, turning them into temporally consistent video super resolution models. We focus on two relevant real-world applications: Simulation of…
Citation impact
- FWCI
- 65.31
- Percentile
- 100%
- References
- 171
Authors
7- ABAndreas BlattmannCorresponding
LMU Klinikum, Ludwig-Maximilians-Universität München
- RRRobin Rombach
Ludwig-Maximilians-Universität München, LMU Klinikum
- HLHuan Ling
University of Toronto, Vector Institute
- TDTim Dockhorn
Vector Institute, University of Waterloo
- SWSeung Wook Kim
University of Toronto, Vector Institute
Topics & keywords
- Computer science
- Leverage (statistics)
- Generator (circuit theory)
- Artificial intelligence
- Focus (optics)
- Computer vision