Markup-to-Image Diffusion Models with Scheduled Sampling
Paper
• 2210.05147 • Published
• 2
Details of this model can be found in our paper on markup-to-image generation. Our code is built on top of HuggingFace diffusers and transformers.
Developed by: Yuntian Deng, Noriyuki Kojima, Alexander M. Rush
Model type: Diffusion-based text-to-image generation model
Language(s): English
License: MIT.
Model Description: This is a model that can be used to generate math formula images based on LaTeX prompts.
Resources for more information: GitHub Repository, Paper.
Cite as:
@inproceedings{
deng2023markuptoimage,
title={Markup-to-Image Diffusion Models with Scheduled Sampling},
author={Yuntian Deng and Noriyuki Kojima and Alexander M Rush},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=81VJDmOE2ol}
}