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In this work, we share three insights for achieving state-of-the-art aesthetic quality in text-to-image generative models.
Generalization and network design strategies
Yann LeCun et al · 1989
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Attributes for classifier feedback
Amar Parkash and Devi Parikh · 2012
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Generative adversarial networks, 2014
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Deep residual learning for image recognition, 2015
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
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Gans trained by a two time-scale update rule converge to a local nash equilibrium, 2018
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2018
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A style-based generator architecture for generative adversarial networks, 2019
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Denoising diffusion probabilistic models, 2020
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Analyzing and improving the image quality of stylegan, 2020
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2020
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Diffusion models beat gans on image synthesis, 2021
Prafulla Dhariwal and Alex Nichol · 2021
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Improved denoising diffusion probabilistic models, 2021
Alex Nichol and Prafulla Dhariwal · 2021
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Score-based generative modeling through stochastic differential equations, 2021
Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2021
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Clipscore: A reference-free evaluation metric for image captioning, 2022
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Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
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How much more data do i need? estimating requirements for downstream tasks
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Variational diffusion models, 2023
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Pick-a-pic: An open dataset of user preferences for text-to-image generation, 2023
Yuval Kirstain, Adam Polyak, Uriel Singer, Shahbuland Matiana, Joe Penna, and Omer Levy · 2023
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Scalable diffusion models with transformers, 2023
William Peebles and Saining Xie · 2023
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Sdxl: Improving latent diffusion models for high-resolution image synthesis, 2023
Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, and Robin Rombach · 2023
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Lima: Less is more for alignment, 2023
Chunting Zhou, Pengfei Liu, Puxin Xu, Srini Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, Susan Zhang, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer, and Omer Levy · 2023
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Laion-5b: An open large-scale dataset for training next generation image-text models, 2022
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, Patrick Schramowski, Srivatsa Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, and Jenia Jitsev · 2022
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Improving image generation with better captions
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Pixart- α \alpha : Fast training of diffusion transformer for photorealistic text-to-image synthesis
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On the importance of noise scheduling for diffusion models, 2023
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Emu: Enhancing image generation models using photogenic needles in a haystack, 2023
Xiaoliang Dai, Ji Hou, Chih-Yao Ma, Sam Tsai, Jialiang Wang, Rui Wang, Peizhao Zhang, Simon Vandenhende, Xiaofang Wang, Abhimanyu Dubey, Matthew Yu, Abhishek Kadian, Filip Radenovic, Dhruv Mahajan, Kunpeng Li, Yue Zhao, Vladan Petrovic, Mitesh Kumar Singh, Simran Motwani, Yi Wen, Yiwen Song, Roshan Sumbaly, Vignesh Ramanathan, Zijian He, Peter Vajda, and Devi Parikh · 2023
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Playground v2
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