Showing 2024Show all
3 papers · 1 filter
cs.CV2024
Harnessing the Latent Diffusion Model for Training-Free Image Style Transfer
Kento Masui, Mayu Otani, Masahiro Nomura +1
Diffusion models have recently shown the ability to generate high-quality images. However, controlling its generation process still poses challenges. The image style transfer task…
cs.CV2024
OpenCOLE: Towards Reproducible Automatic Graphic Design Generation
Naoto Inoue, Kento Masui, Wataru Shimoda +1
Automatic generation of graphic designs has recently received considerable attention. However, the state-of-the-art approaches are complex and rely on proprietary datasets, which c…
cs.CV2024
LayoutFlow: Flow Matching for Layout Generation
Julian Jorge Andrade Guerreiro, Naoto Inoue, Kento Masui +2
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…