LayoutFlow: Flow Matching for Layout Generation
<|reference_start|>LayoutFlow: Flow Matching for Layout Generation: Finding a suitable layout represents a crucial task for diverse applications in graphic design. Motivated by simpler and smoother sampling trajectories, we explore the use of Flow Matching as an alternative to current diffusion-based layout generation models. Specifically, we propose LayoutFlow, an efficient flow-based model capable of generating high-quality layouts. Instead of progressively denoising the elements of a noisy layout, our method learns to gradually move, or flow, the elements of an initial sample until it reaches its final prediction. In addition, we employ a conditioning scheme that allows us to handle various generation tasks with varying degrees of conditioning with a single model. Empirically, LayoutFlow performs on par with state-of-the-art models while being significantly faster.<|reference_end|>
@article{guerreiro2024layoutflow:,
    title={LayoutFlow: Flow Matching for Layout Generation},
    author={Julian Jorge Andrade Guerreiro, Naoto Inoue, Kento Masui, Mayu Otani
  and Hideki Nakayama},
    journal={arXiv preprint arXiv:2403.18187},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.18187},
    primaryClass={cs.CV}
}