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Diffusion models: A comprehensive survey of methods and applications
Diffusion models have emerged as a powerful new family of deep generative models with
record-breaking performance in many applications, including image synthesis, video …
record-breaking performance in many applications, including image synthesis, video …
Diffusion models in bioinformatics and computational biology
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 …
applied in computer vision, natural language processing and bioinformatics. In this Review …
Sdxl: Improving latent diffusion models for high-resolution image synthesis
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 …
previous versions of Stable Diffusion, SDXL leverages a three times larger UNet backbone …
Align your latents: High-resolution video synthesis with latent diffusion models
Abstract Latent Diffusion Models (LDMs) enable high-quality image synthesis while avoiding
excessive compute demands by training a diffusion model in a compressed lower …
excessive compute demands by training a diffusion model in a compressed lower …
Stable video diffusion: Scaling latent video diffusion models to large datasets
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 …
the-art text-to-video and image-to-video generation. Recently, latent diffusion models trained …
Scaling rectified flow transformers for high-resolution image synthesis
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 …
and have emerged as a powerful generative modeling technique for high-dimensional …
Latent consistency models: Synthesizing high-resolution images with few-step inference
Latent Diffusion models (LDMs) have achieved remarkable results in synthesizing high-
resolution images. However, the iterative sampling process is computationally intensive and …
resolution images. However, the iterative sampling process is computationally intensive and …
Scalable diffusion models with transformers
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 …
latent diffusion models of images, replacing the commonly-used U-Net backbone with a …
One-step diffusion with distribution matching distillation
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 …
introduce Distribution Matching Distillation (DMD) a procedure to transform a diffusion model …
Score jacobian chaining: Lifting pretrained 2d diffusion models for 3d generation
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 …
on the learned gradients, and back-propagate the score of a diffusion model through the …