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Latent diffusion models have become the popular choice for scaling up diffusion models for high resolution image synthesis.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Fully convolutional networks for semantic segmentation
Evan Shelhamer, Jonathan Long, and Trevor Darrell · 2016
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Glow: Generative flow with invertible 1x1 convolutions
Durk P Kingma and Prafulla Dhariwal · 2018
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Distribution augmentation for generative modeling
Heewoo Jun, Rewon Child, Mark Chen, John Schulman, Aditya Ramesh, Alec Radford, and Ilya Sutskever · 2020
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alex Nichol · 2021
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2021
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Diederik P. Kingma, Tim Salimans, Ben Poole, and Jonathan Ho · 2021
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2021
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Tackling the generative learning trilemma with denoising diffusion gans
Zhisheng Xiao, Karsten Kreis, and Arash Vahdat · 2021
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ediff-i: Text-to-image diffusion models with an ensemble of expert denoisers
Yogesh Balaji, Seungjun Nah, Xun Huang, Arash Vahdat, Jiaming Song, Karsten Kreis, Miika Aittala, Timo Aila, Samuli Laine, Bryan Catanzaro, Tero Karras, and Ming-Yu Liu · 2022
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f-dm: A multi-stage diffusion model via progressive signal transformation
Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Miguel Ángel Bautista, and Josh M. Susskind · 2022
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Video diffusion models
Jonathan Ho, Tim Salimans, Alexey A. Gritsenko, William Chan, Mohammad Norouzi, and David J. Fleet · 2022
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Scalable adaptive computation for iterative generation
Allan Jabri, David J. Fleet, and Ting Chen · 2022
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Elucidating the design space of diffusion-based generative models
Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
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Scalable diffusion models with transformers
William Peebles and Saining Xie · 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
Cited alongside, same era.
Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S. Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J. Fleet, and Mohammad Norouzi · 2022
Cited alongside, same era.
Progressive distillation for fast sampling of diffusion models
Tim Salimans and Jonathan Ho · 2022
Cited alongside, same era.
Stylegan-xl: Scaling stylegan to large diverse datasets
Axel Sauer, Katja Schwarz, and Andreas Geiger · 2022
Cited alongside, same era.
All are worth words: A vit backbone for diffusion models
Fan Bao, Shen Nie, Kaiwen Xue, Yue Cao, Chongxuan Li, Hang Su, and Jun Zhu · 2023
Cited alongside, same era.
One-step diffusion with distribution matching distillation
Tianwei Yin, Michaël Gharbi, Richard Zhang, Eli Shechtman, Fredo Durand, William T Freeman, and Taesung Park · 2023
Later among the works it cites.
Photorealistic video generation with diffusion models
Agrim Gupta, Lijun Yu, Kihyuk Sohn, Xiuye Gu, Meera Hahn, Fei-Fei Li, Irfan Essa, Lu Jiang, and José Lezama · 2024
Closest in time.
Jonathan Heek, Emiel Hoogeboom, and Tim Salimans · 2024
Closest in time.
Guiding a diffusion model with a bad version of itself
Tero Karras, Miika Aittala, Tuomas Kynkäänniemi, Jaakko Lehtinen, Timo Aila, and Samuli Laine · 2024
Closest in time.
Applying guidance in a limited interval improves sample and distribution quality in diffusion models
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On the importance of noise scheduling for diffusion models
Ting Chen · 2023
Cited alongside, same era.
Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Josh M. Susskind, and Navdeep Jaitly · 2023
Cited alongside, same era.
Diffit: Diffusion vision transformers for image generation
Ali Hatamizadeh, Jiaming Song, Guilin Liu, Jan Kautz, and Arash Vahdat · 2023
Cited alongside, same era.
simple diffusion: End-to-end diffusion for high resolution images
Emiel Hoogeboom, Jonathan Heek, and Tim Salimans · 2023
Cited alongside, same era.
Scalelong: Towards more stable training of diffusion model via scaling network long skip connection
Zhongzhan Huang, Zhou Pan, Shuicheng Yan, and Liang Lin · 2023
Cited alongside, same era.
Scedit: Efficient and controllable image diffusion generation via skip connection editing
Zeyinzi Jiang, Chaojie Mao, Yulin Pan, Zhen Han, and Jingfeng Zhang · 2023
Cited alongside, same era.
Analyzing and improving the training dynamics of diffusion models
Tero Karras, Miika Aittala, Jaakko Lehtinen, Janne Hellsten, Timo Aila, and Samuli Laine · 2023
Cited alongside, same era.
Tuomas Kynkäänniemi, Miika Aittala, Tero Karras, Samuli Laine, Timo Aila, and Jaakko Lehtinen · 2024
Closest in time.
Diff-instruct: A universal approach for transferring knowledge from pre-trained diffusion models
Weijian Luo, Tianyang Hu, Shifeng Zhang, Jiacheng Sun, Zhenguo Li, and Zhihua Zhang · 2024
Closest in time.
The surprising effectiveness of skip-tuning in diffusion sampling
Jiajun Ma, Shuchen Xue, Tianyang Hu, Wenjia Wang, Zhaoqiang Liu, Zhenguo Li, Zhi-Ming Ma, and Kenji Kawaguchi · 2024
Closest in time.
Rolling diffusion models
David Ruhe, Jonathan Heek, Tim Salimans, and Emiel Hoogeboom · 2024
Closest in time.
Multistep distillation of diffusion models via moment matching
Tim Salimans, Thomas Mensink, Jonathan Heek, and Emiel Hoogeboom · 2024
Closest in time.
Relay diffusion: Unifying diffusion process across resolutions for image synthesis
Jiayan Teng, Wendi Zheng, Ming Ding, Wenyi Hong, Jianqiao Wangni, Zhuoyi Yang, and Jie Tang · 2024
Closest in time.
Haoning Wu, Shaocheng Shen, Qiang Hu, Xiaoyun Zhang, Ya Zhang, and Yanfeng Wang · 2024
Closest in time.
Disco-diff: Enhancing continuous diffusion models with discrete latents
Yilun Xu, Gabriele Corso, Tommi S. Jaakkola, Arash Vahdat, and Karsten Kreis · 2024
Closest in time.
Improved distribution matching distillation for fast image synthesis
Tianwei Yin, Michaël Gharbi, Taesung Park, Richard Zhang, Eli Shechtman, Frédo Durand, and William T. Freeman · 2024
Closest in time.
Language model beats diffusion - tokenizer is key to visual generation
Lijun Yu, José Lezama, Nitesh Bharadwaj Gundavarapu, Luca Versari, Kihyuk Sohn, David Minnen, Yong Cheng, Agrim Gupta, Xiuye Gu, Alexander G. Hauptmann, Boqing Gong, Ming-Hsuan Yang, Irfan Essa, David A. Ross, and Lu Jiang · 2024
Closest in time.
Cogview3: Finer and faster text-to-image generation via relay diffusion
Wendi Zheng, Jiayan Teng, Zhuoyi Yang, Weihan Wang, Jidong Chen, Xiaotao Gu, Yuxiao Dong, Ming Ding, and Jie Tang · 2024
Closest in time.