736 citations · 1.4k across the 20 of their papers we have counts for
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DiffusionSat: A Generative Foundation Model for Satellite Imagery
Samar Khanna, Patrick Liu, Linqi Zhou +5
Diffusion models have achieved state-of-the-art results on many modalities including images, speech, and video. However, existing models are not tailored to support remote sensing…
Adversarial Diffusion Distillation
Axel Sauer, Dominik Lorenz, Andreas Blattmann +1
We introduce Adversarial Diffusion Distillation (ADD), a novel training approach that efficiently samples large-scale foundational image diffusion models in just 1-4 steps while ma…
SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
Dustin Podell, Zion English, Kyle Lacey +5
We present SDXL, a latent diffusion model for text-to-image synthesis. Compared to previous versions of Stable Diffusion, SDXL leverages a three times larger UNet backbone: The inc…
NeuralField-LDM: Scene Generation with Hierarchical Latent Diffusion Models
Seung Wook Kim, Bradley Brown, Kangxue Yin +6
Automatically generating high-quality real world 3D scenes is of enormous interest for applications such as virtual reality and robotics simulation. Towards this goal, we introduce…
Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models
Andreas Blattmann, Robin Rombach, Huan Ling +4
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 s…