77 citations · 137 across the 22 of their papers we have counts for
23 papers
OnomatoBridge: Onomatopoeia Translation and Rendering Pipeline in Manga
Takara Taniguchi, Wataru Shimoda, Kota Yamaguchi +1
Manga is a comic drawn by black and white paints gaining popularity around the world. Onomatopoeia in Manga specifically appeals to the audience with its unique visual styles, whic…
Automatic Text Box Placement for Supporting Typographic Design
Jun Muraoka, Daichi Haraguchi, Naoto Inoue +3
In layout design for advertisements and web pages, balancing visual appeal and communication efficiency is crucial. This study examines automated text box placement in incomplete l…
OTR: Synthesizing Overlay Text Dataset for Text Removal
Jan Zdenek, Wataru Shimoda, Kota Yamaguchi
Text removal is a crucial task in computer vision with applications such as privacy preservation, image editing, and media reuse. While existing research has primarily focused on s…
OnomatoGen: Onomatopoeia Generation with the Alpha-Channel in Manga
Takara Taniguchi, Wataru Shimoda, Kota Yamaguchi +1
Onomatopoeia is an important element for textual messaging in manga. Unlike character dialogue in manga, onomatopoeic expressions are visually stylized, with variations in shape, s…
Type-R: Automatically Retouching Typos for Text-to-Image Generation
Wataru Shimoda, Naoto Inoue, Daichi Haraguchi +3
While recent text-to-image models can generate photorealistic images from text prompts that reflect detailed instructions, they still face significant challenges in accurately rend…
Can GPTs Evaluate Graphic Design Based on Design Principles?
Daichi Haraguchi, Naoto Inoue, Wataru Shimoda +3
Recent advancements in foundation models show promising capability in graphic design generation. Several studies have started employing Large Multimodal Models (LMMs) to evaluate g…
Multimodal Markup Document Models for Graphic Design Completion
Kotaro Kikuchi, Ukyo Honda, Naoto Inoue +3
We introduce MarkupDM, a multimodal markup document model that represents graphic design as an interleaved multimodal document consisting of both markup language and images. Unlike…
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…
Total Disentanglement of Font Images into Style and Character Class Features
Daichi Haraguchi, Wataru Shimoda, Kota Yamaguchi +1
In this paper, we demonstrate a total disentanglement of font images. Total disentanglement is a neural network-based method for decomposing each font image nonlinearly and complet…
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 Diverse and Consistent Typography Generation
Wataru Shimoda, Daichi Haraguchi, Seiichi Uchida +1
In this work, we consider the typography generation task that aims at producing diverse typographic styling for the given graphic document. We formulate typography generation as a…
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…
De-rendering Stylized Texts
Wataru Shimoda, Daichi Haraguchi, Seiichi Uchida +1
Editing raster text is a promising but challenging task. We propose to apply text vectorization for the task of raster text editing in display media, such as posters, web pages, or…
CanvasVAE: Learning to Generate Vector Graphic Documents
Kota Yamaguchi
Vector graphic documents present visual elements in a resolution free, compact format and are often seen in creative applications. In this work, we attempt to learn a generative mo…
Constrained Graphic Layout Generation via Latent Optimization
Kotaro Kikuchi, Edgar Simo-Serra, Mayu Otani +1
It is common in graphic design humans visually arrange various elements according to their design intent and semantics. For example, a title text almost always appears on top of ot…
Serif or Sans: Visual Font Analytics on Book Covers and Online Advertisements
Yuto Shinahara, Takuro Karamatsu, Daisuke Harada +2
In this paper, we conduct a large-scale study of font statistics in book covers and online advertisements. Through the statistical study, we try to understand how graphic designers…
Recommending Outfits from Personal Closet
Pongsate Tangseng, Kota Yamaguchi, Takayuki Okatani
We consider grading a fashion outfit for recommendation, where we assume that users have a closet of items and we aim at producing a score for an arbitrary combination of items in…
Feedback-prop: Convolutional Neural Network Inference under Partial Evidence
Tianlu Wang, Kota Yamaguchi, Vicente Ordonez
We propose an inference procedure for deep convolutional neural networks (CNNs) when partial evidence is available. Our method consists of a general feedback-based propagation appr…
End-to-end learning potentials for structured attribute prediction
Kota Yamaguchi, Takayuki Okatani, Takayuki Umeda +2
We present a structured inference approach in deep neural networks for multiple attribute prediction. In attribute prediction, a common approach is to learn independent classifiers…
Looking at Outfit to Parse Clothing
Pongsate Tangseng, Zhipeng Wu, Kota Yamaguchi
This paper extends fully-convolutional neural networks (FCN) for the clothing parsing problem. Clothing parsing requires higher-level knowledge on clothing semantics and contextual…
Automatic Attribute Discovery with Neural Activations
Sirion Vittayakorn, Takayuki Umeda, Kazuhiko Murasaki +3
How can a machine learn to recognize visual attributes emerging out of online community without a definitive supervised dataset? This paper proposes an automatic approach to discov…