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While conditional diffusion models are known to have good coverage of the data distribution, they still face limitations in output diversity, particularly when sampled with a high classifier-free guidance scale for optimal image quality or when trained on small datasets.
Generative adversarial networks
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, and Yoshua Bengio · 2014
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Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Wavegrad: Estimating gradients for waveform generation
Nanxin Chen, Yu Zhang, Heiga Zen, Ron J. Weiss, Mohammad Norouzi, and William Chan · 2021
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Diffusion models beat gans on image synthesis
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Zhifeng Kong, Wei Ping, Jiaji Huang, Kexin Zhao, and Bryan Catanzaro · 2021
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Alexander Quinn Nichol and Prafulla Dhariwal · 2021
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Ting Chen · 2023
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Masked diffusion transformer is a strong image synthesizer
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Classifier-free diffusion guidance
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