Diffusion models: A comprehensive survey of methods and applications

L Yang, Z Zhang, Y Song, S Hong, R Xu, Y Zhao… - ACM Computing …, 2023‏ - dl.acm.org
Diffusion models have emerged as a powerful new family of deep generative models with
record-breaking performance in many applications, including image synthesis, video …

Diffusion models in bioinformatics and computational biology

Z Guo, J Liu, Y Wang, M Chen, D Wang, D Xu… - Nature reviews …, 2024‏ - nature.com
Denoising diffusion models embody a type of generative artificial intelligence that can be
applied in computer vision, natural language processing and bioinformatics. In this Review …

Sdxl: Improving latent diffusion models for high-resolution image synthesis

D Podell, Z English, K Lacey, A Blattmann… - arxiv preprint arxiv …, 2023‏ - arxiv.org
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 …

Align your latents: High-resolution video synthesis with latent diffusion models

A Blattmann, R Rombach, H Ling… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
Abstract Latent Diffusion Models (LDMs) enable high-quality image synthesis while avoiding
excessive compute demands by training a diffusion model in a compressed lower …

Stable video diffusion: Scaling latent video diffusion models to large datasets

A Blattmann, T Dockhorn, S Kulal… - arxiv preprint arxiv …, 2023‏ - arxiv.org
We present Stable Video Diffusion-a latent video diffusion model for high-resolution, state-of-
the-art text-to-video and image-to-video generation. Recently, latent diffusion models trained …

Scaling rectified flow transformers for high-resolution image synthesis

P Esser, S Kulal, A Blattmann, R Entezari… - … on machine learning, 2024‏ - openreview.net
Diffusion models create data from noise by inverting the forward paths of data towards noise
and have emerged as a powerful generative modeling technique for high-dimensional …

Latent consistency models: Synthesizing high-resolution images with few-step inference

S Luo, Y Tan, L Huang, J Li, H Zhao - arxiv preprint arxiv:2310.04378, 2023‏ - arxiv.org
Latent Diffusion models (LDMs) have achieved remarkable results in synthesizing high-
resolution images. However, the iterative sampling process is computationally intensive and …

Scalable diffusion models with transformers

W Peebles, S **e - Proceedings of the IEEE/CVF …, 2023‏ - openaccess.thecvf.com
We explore a new class of diffusion models based on the transformer architecture. We train
latent diffusion models of images, replacing the commonly-used U-Net backbone with a …

One-step diffusion with distribution matching distillation

T Yin, M Gharbi, R Zhang… - Proceedings of the …, 2024‏ - openaccess.thecvf.com
Diffusion models generate high-quality images but require dozens of forward passes. We
introduce Distribution Matching Distillation (DMD) a procedure to transform a diffusion model …

Score jacobian chaining: Lifting pretrained 2d diffusion models for 3d generation

H Wang, X Du, J Li, RA Yeh… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
A diffusion model learns to predict a vector field of gradients. We propose to apply chain rule
on the learned gradients, and back-propagate the score of a diffusion model through the …