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20162022
most citedDenoising Diffusion Probabilistic Models

5.7k citations · 11.9k across the 19 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

cs.CV2022★ 63 cited

Novel View Synthesis with Diffusion Models

Daniel Watson, William Chan, Ricardo Martin-Brualla +3

We present 3DiM, a diffusion model for 3D novel view synthesis, which is able to translate a single input view into consistent and sharp completions across many views. The core com…

cs.CV2022★ 346 cited

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…

cs.CV2022★ 10 cited

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…

cs.LG2022★ 750 cited

Classifier-Free Diffusion Guidance

Jonathan Ho, Tim Salimans

Classifier guidance is a recently introduced method to trade off mode coverage and sample fidelity in conditional diffusion models post training, in the same spirit as low temperat…

cs.CV2022★ 2.1k cited

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…

cs.LG2022★ 23 cited

Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality

Daniel Watson, William Chan, Jonathan Ho +1

Diffusion models have emerged as an expressive family of generative models rivaling GANs in sample quality and autoregressive models in likelihood scores. Standard diffusion models…