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We propose a diffusion distillation method that achieves new state-of-the-art in one-step/few-step 1024px text-to-image generation based on SDXL.
Generative adversarial networks
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Group normalization
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The unreasonable effectiveness of deep features as a perceptual metric
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MSG-GAN: multi-scale gradients for generative adversarial networks
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The lipschitz constant of self-attention
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High-resolution image synthesis with latent diffusion models
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Projected gans converge faster
Axel Sauer, Kashyap Chitta, Jens Müller, and Andreas Geiger · 2021
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 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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Ben Poole, Ajay Jain, Jonathan T. Barron, and Ben Mildenhall · 2023
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Stylegan-t: Unlocking the power of gans for fast large-scale text-to-image synthesis
Axel Sauer, Tero Karras, Samuli Laine, Andreas Geiger, and Timo Aila · 2023
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Adversarial diffusion distillation, 2023
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Make-a-video: Text-to-video generation without text-video data
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Consistency models
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Ip-adapter: Text compatible image prompt adapter for text-to-image diffusion models, 2023
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One-step diffusion with distribution matching distillation, 2023
Tianwei Yin, Michaël Gharbi, Richard Zhang, Eli Shechtman, Fredo Durand, William T. Freeman, and Taesung Park · 2023
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Adding conditional control to text-to-image diffusion models
Lvmin Zhang, Anyi Rao, and Maneesh Agrawala · 2023
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Wenliang Zhao, Lujia Bai, Yongming Rao, Jie Zhou, and Jiwen Lu · 2023
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Magicvideo: Efficient video generation with latent diffusion models, 2023
Daquan Zhou, Weimin Wang, Hanshu Yan, Weiwei Lv, Yizhe Zhu, and Jiashi Feng · 2023
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Pixart-$\alpha$: Fast training of diffusion transformer for photorealistic text-to-image synthesis
Junsong Chen, Jincheng YU, Chongjian GE, Lewei Yao, Enze Xie, Zhongdao Wang, James Kwok, Ping Luo, Huchuan Lu, and Zhenguo Li · 2024
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Common diffusion noise schedules and sample steps are flawed
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Diffusion model with perceptual loss, 2024
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DINOv2: Learning robust visual features without supervision
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Pablo Pernias, Dominic Rampas, Mats Leon Richter, Christopher Pal, and Marc Aubreville · 2024
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Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, and Robin Rombach · 2024
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Improved techniques for training consistency models
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