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Advances in latent diffusion models (LDMs) have revolutionized high-resolution image generation, but the design space of the autoencoder that is central to these systems remains underexplored.
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Tiantong Guo, Hojjat Seyed Mousavi, Tiep Huu Vu, and Vishal Monga · 2017
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Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Huaibo Huang, Ran He, Zhenan Sun, and Tieniu Tan · 2017
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Generative modeling by estimating gradients of the data distribution
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William Peebles and Saining Xie · 2022
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Hierarchical text-conditional image generation with CLIP latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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simple diffusion: End-to-end diffusion for high resolution images
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I 2 {}^{\mbox{2}} sb: Image-to-image schrödinger bridge
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Scaling rectified flow transformers for high-resolution image synthesis
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