no code implementations • 19 Mar 2024 • Daichi Haraguchi, Wataru Shimoda, Kota Yamaguchi, Seiichi Uchida
Second, it is demonstrated that the disentangled features produced by total disentanglement apply to a variety of tasks, including font recognition, character recognition, and one-shot font image generation.
no code implementations • 13 Oct 2023 • Takumi Nishiyasu, Wataru Shimoda, Yoichi Sato
We explore two derived approaches, a proposal-based approach, and a heatmap-based approach, and we construct a dataset for evaluating the performance of the proposed approaches on image cropping under design constraints.
no code implementations • 5 Sep 2023 • Wataru Shimoda, Daichi Haraguchi, Seiichi Uchida, Kota Yamaguchi
In this work, we consider the typography generation task that aims at producing diverse typographic styling for the given graphic document.
1 code implementation • ICCV 2021 • Wataru Shimoda, Daichi Haraguchi, Seiichi Uchida, Kota Yamaguchi
Editing raster text is a promising but challenging task.
1 code implementation • ICCV 2019 • Wataru Shimoda, Keiji Yanai
In this paper, to make the most of such mapping functions, we assume that the results of the mapping function include noise, and we improve the accuracy by removing noise.
Ranked #24 on Semantic Segmentation on PASCAL VOC 2012 val
no code implementations • 4 Jul 2018 • Nevrez Imamoglu, Wataru Shimoda, Chi Zhang, Yuming Fang, Asako Kanezaki, Keiji Yanai, Yoshifumi Nishida
Bottom-up and top-down visual cues are two types of information that helps the visual saliency models.
1 code implementation • 1 Mar 2017 • Nevrez Imamoglu, Chi Zhang, Wataru Shimoda, Yuming Fang, Boxin Shi
As prior knowledge of objects or object features helps us make relations for similar objects on attentional tasks, pre-trained deep convolutional neural networks (CNNs) can be used to detect salient objects on images regardless of the object class is in the network knowledge or not.