# Contrast-augmented Diffusion Model with Fine-grained Sequence Alignment for Markup-to-Image Generation

Guojin Zhong, Jin Yuan, Pan Wang, Kailun Yang, Weili Guan, Zhiyong Li. ACM Multimedia 2023 (2023).

FSA-CDM combines fine-grained cross-modal sequence alignment, contextual modeling, and a contrast-augmented diffusion objective for markup-to-image generation.

A subsequent markup-to-image method that builds on the task and four datasets introduced by Deng, Kojima, and Rush, addressing alignment and contrastive feedback.

[Original paper](https://arxiv.org/abs/2308.01147)

## Citation

```bibtex
@inproceedings{zhong2023contrastaugmented,
  title = {{Contrast-augmented Diffusion Model with Fine-grained Sequence Alignment for Markup-to-Image Generation}},
  author = {Zhong, Guojin and Yuan, Jin and Wang, Pan and Yang, Kailun and Guan, Weili and Li, Zhiyong},
  year = {2023},
  booktitle = {ACM Multimedia 2023},
  url = {https://arxiv.org/abs/2308.01147},
  eprint = {2308.01147},
  archivePrefix = {arXiv}
}
```