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Image Synthesis
Taming Transformers for High-Resolution Image Synthesis
Published:12/18/2020
Generative Adversarial Policy OptimizationDiffusion ModelsImage Super-resolutionImage Synthesis
This study combines CNN's inductive bias with Transformer expressivity to synthesize highresolution images. It first learns a contextrich vocabulary of image constituents with CNNs, then models their composition using Transformers, achieving stateoftheart results in semantic
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Denoising Diffusion Probabilistic Models
Published:6/20/2020
Diffusion ModelsImage SynthesisTraining-Free Acceleration MethodsCIFAR10 DatasetProgressive Lossy Decompression
The paper presents a novel denoising diffusion probabilistic model inspired by nonequilibrium thermodynamics, achieving highquality image synthesis. By training on a weighted variational bound, it establishes a new connection with denoising score matching, attaining competitive
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