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We present DiffCollage, a compositional diffusion model that can generate large content by leveraging diffusion models trained on generating pieces of the large content.
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Diffusion models beat gans on image synthesis
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Taming transformers for high-resolution image synthesis
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Snips: Solving noisy inverse problems stochastically
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GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen · 2021
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Exploiting deep generative prior for versatile image restoration and manipulation
Xingang Pan, Xiaohang Zhan, Bo Dai, Dahua Lin, Chen Change Loy, and Ping Luo · 2021
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Denoising diffusion restoration models
Bahjat Kawar, Michael Elad, Stefano Ermon, and Jiaming Song · 2022
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Imagic: Text-based real image editing with diffusion models
Bahjat Kawar, Shiran Zada, Oran Lang, Omer Tov, Huiwen Chang, Tali Dekel, Inbar Mosseri, and Michal Irani · 2022
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Diffusion-lm improves controllable text generation
Xiang Lisa Li, John Thickstun, Ishaan Gulrajani, Percy Liang, and Tatsunori B Hashimoto · 2022
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Score-Based Generative Modeling through Stochastic Differential Equations
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Csdi: Conditional score-based diffusion models for probabilistic time series imputation
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High-resolution image synthesis with latent diffusion models
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Pyramidal denoising diffusion probabilistic models
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Palette: Image-to-image diffusion models
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Photorealistic text-to-image diffusion models with deep language understanding
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UniTune: Text-driven image editing by fine tuning an image generation model on a single image
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Nuwa-infinity: Autoregressive over autoregressive generation for infinite visual synthesis
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First hitting diffusion models
Mao Ye, Lemeng Wu, and Qiang Liu · 2022
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Lion: Latent point diffusion models for 3d shape generation
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Fast sampling of diffusion models with exponential integrator
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gddim: Generalized denoising diffusion implicit models
Qinsheng Zhang, Molei Tao, and Yongxin Chen · 2022
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