MARS: Mixture of Auto-Regressive Models for Fine-grained Text-to-image Synthesis

doi:doi:10.57702/hwlngj8p

MARS: Mixture of Auto-Regressive Models for Fine-grained Text-to-image Synthesis

MARS is an innovative auto-regressive framework that not only retains the capabilities of pre-trained Large Language Models (LLMs) but also incorporates top-tier text-to-image (T2I) generation proficiency.

Data and Resources

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The json representation of the dataset with its distributions based on DCAT.
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Wanggui He, Siming Fu, Mushui Liu, Xierui Wang, Wenyi Xiao, Fangxun Shu, Yi Wang, Lei Zhang, Zhelun Yu, Haoyuan Li, Ziwei Huang, LeiLei Gan, Hao Jiang (2024). Dataset: MARS: Mixture of Auto-Regressive Models for Fine-grained Text-to-image Synthesis. https://doi.org/10.57702/hwlngj8p

DOI retrieved: December 16, 2024

Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Author	Wanggui He
More Authors	Siming Fu Mushui Liu Xierui Wang Wenyi Xiao Fangxun Shu Yi Wang Lei Zhang Zhelun Yu Haoyuan Li Ziwei Huang LeiLei Gan Hao Jiang
Homepage	https://github.com/fusiming3/MARS