4 papers · 1 filter
MangaDiT: Reference-Guided Line Art Colorization with Hierarchical Attention in Diffusion Transformers
Qianru Qiu, Jiafeng Mao, Kento Masui +1
Recent advances in diffusion models have significantly improved the performance of reference-guided line art colorization. However, existing methods still struggle with region-leve…
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…
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…
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…