81 citations · 102 across the 11 of their papers we have counts for
11 papers
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…
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…
Retrieval-Augmented Layout Transformer for Content-Aware Layout Generation
Daichi Horita, Naoto Inoue, Kotaro Kikuchi +2
Content-aware graphic layout generation aims to automatically arrange visual elements along with a given content, such as an e-commerce product image. In this paper, we argue that…
Towards Flexible Multi-modal Document Models
Naoto Inoue, Kotaro Kikuchi, Edgar Simo-Serra +2
Creative workflows for generating graphical documents involve complex inter-related tasks, such as aligning elements, choosing appropriate fonts, or employing aesthetically harmoni…
LayoutDM: Discrete Diffusion Model for Controllable Layout Generation
Naoto Inoue, Kotaro Kikuchi, Edgar Simo-Serra +2
Controllable layout generation aims at synthesizing plausible arrangement of element bounding boxes with optional constraints, such as type or position of a specific element. In th…
Generative Colorization of Structured Mobile Web Pages
Kotaro Kikuchi, Naoto Inoue, Mayu Otani +2
Color is a critical design factor for web pages, affecting important factors such as viewer emotions and the overall trust and satisfaction of a website. Effective coloring require…
Learning from Synthetic Shadows for Shadow Detection and Removal
Naoto Inoue, Toshihiko Yamasaki
Shadow removal is an essential task in computer vision and computer graphics. Recent shadow removal approaches all train convolutional neural networks (CNN) on real paired shadow/s…
Augmented Cyclic Consistency Regularization for Unpaired Image-to-Image Translation
Takehiko Ohkawa, Naoto Inoue, Hirokatsu Kataoka +1
Unpaired image-to-image (I2I) translation has received considerable attention in pattern recognition and computer vision because of recent advancements in generative adversarial ne…
PixelRL: Fully Convolutional Network with Reinforcement Learning for Image Processing
Ryosuke Furuta, Naoto Inoue, Toshihiko Yamasaki
This paper tackles a new problem setting: reinforcement learning with pixel-wise rewards (pixelRL) for image processing. After the introduction of the deep Q-network, deep RL has b…
Fully Convolutional Network with Multi-Step Reinforcement Learning for Image Processing
Ryosuke Furuta, Naoto Inoue, Toshihiko Yamasaki
This paper tackles a new problem setting: reinforcement learning with pixel-wise rewards (pixelRL) for image processing. After the introduction of the deep Q-network, deep RL has b…
Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation
Naoto Inoue, Ryosuke Furuta, Toshihiko Yamasaki +1
Can we detect common objects in a variety of image domains without instance-level annotations? In this paper, we present a framework for a novel task, cross-domain weakly supervise…