2.1k citations · 9.7k across the 40 of their papers we have counts for
9 papers · 1 filter
Simpler Diffusion (SiD2): 1.5 FID on ImageNet512 with pixel-space diffusion
Emiel Hoogeboom, Thomas Mensink, Jonathan Heek +3
Latent diffusion models have become the popular choice for scaling up diffusion models for high resolution image synthesis. Compared to pixel-space models that are trained end-to-e…
Imagen 3
Imagen-Team-Google, :, Jason Baldridge +257
We introduce Imagen 3, a latent diffusion model that generates high quality images from text prompts. We describe our quality and responsibility evaluations. Imagen 3 is preferred…
Simple diffusion: End-to-end diffusion for high resolution images
Emiel Hoogeboom, Jonathan Heek, Tim Salimans
Currently, applying diffusion models in pixel space of high resolution images is difficult. Instead, existing approaches focus on diffusion in lower dimensional spaces (latent diff…
Imagen Video: High Definition Video Generation with Diffusion Models
Jonathan Ho, William Chan, Chitwan Saharia +8
We present Imagen Video, a text-conditional video generation system based on a cascade of video diffusion models. Given a text prompt, Imagen Video generates high definition videos…
On Distillation of Guided Diffusion Models
Chenlin Meng, Robin Rombach, Ruiqi Gao +4
Classifier-free guided diffusion models have recently been shown to be highly effective at high-resolution image generation, and they have been widely used in large-scale diffusion…
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
Chitwan Saharia, William Chan, Saurabh Saxena +11
We present Imagen, a text-to-image diffusion model with an unprecedented degree of photorealism and a deep level of language understanding. Imagen builds on the power of large tran…
Cascaded Diffusion Models for High Fidelity Image Generation
Jonathan Ho, Chitwan Saharia, William Chan +3
We show that cascaded diffusion models are capable of generating high fidelity images on the class-conditional ImageNet generation benchmark, without any assistance from auxiliary…
Milking CowMask for Semi-Supervised Image Classification
Geoff French, Avital Oliver, Tim Salimans
Consistency regularization is a technique for semi-supervised learning that underlies a number of strong results for classification with few labeled data. It works by encouraging a…
Axial Attention in Multidimensional Transformers
Jonathan Ho, Nal Kalchbrenner, Dirk Weissenborn +1
We propose Axial Transformers, a self-attention-based autoregressive model for images and other data organized as high dimensional tensors. Existing autoregressive models either su…