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Fonts have huge variations in their styles and give readers different impressions. Therefore, generating new fonts is worthy of giving new impressions to readers. In this paper, we employ diffusion models to generate new font styles by…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 Tetta Kondo , Shumpei Takezaki , Daichi Haraguchi , Seiichi Uchida

Recent deep learning based approaches have achieved great success on handwriting recognition. Chinese characters are among the most widely adopted writing systems in the world. Previous research has mainly focused on recognizing handwritten…

Computer Vision and Pattern Recognition · Computer Science 2016-06-22 Xu-Yao Zhang , Fei Yin , Yan-Ming Zhang , Cheng-Lin Liu , Yoshua Bengio

Deciphering oracle bone scripts plays an important role in Chinese archaeology and philology. However, a significant challenge remains due to the scarcity of oracle character images. To overcome this issue, we propose Diff-Oracle, a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Jing Li , Qiu-Feng Wang , Siyuan Wang , Rui Zhang , Kaizhu Huang , Erik Cambria

Diffusion models have become a new generative paradigm for text generation. Considering the discrete categorical nature of text, in this paper, we propose GlyphDiffusion, a novel diffusion approach for text generation via text-guided image…

Computation and Language · Computer Science 2023-05-09 Junyi Li , Wayne Xin Zhao , Jian-Yun Nie , Ji-Rong Wen

Chinese font generation aims to create a new Chinese font library based on some reference samples. It is a topic of great concern to many font designers and typographers. Over the past years, with the rapid development of deep learning…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Weiran Chen , Guiqian Zhu , Ying Li , Yi Ji , Chunping Liu

Creating graphic layouts is a fundamental step in graphic designs. In this work, we present a novel generative model named LayoutDiffusion for automatic layout generation. As layout is typically represented as a sequence of discrete tokens,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-16 Junyi Zhang , Jiaqi Guo , Shizhao Sun , Jian-Guang Lou , Dongmei Zhang

Content and style disentanglement is an effective way to achieve few-shot font generation. It allows to transfer the style of the font image in a source domain to the style defined with a few reference images in a target domain. However,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Chi Wang , Min Zhou , Tiezheng Ge , Yuning Jiang , Hujun Bao , Weiwei Xu

Diffusion models have emerged as a prominent technique in generative modeling with neural networks, making their mark in tasks like text-to-image translation and super-resolution. In this tutorial, we provide a comprehensive guide to build…

Image and Video Processing · Electrical Eng. & Systems 2025-01-24 Harshith Bachimanchi , Giovanni Volpe

Probabilistic denoising diffusion models (DDMs) have set a new standard for 2D image generation. Extending DDMs for 3D content creation is an active field of research. Here, we propose TetraDiffusion, a diffusion model that operates on a…

Computer Vision and Pattern Recognition · Computer Science 2024-08-12 Nikolai Kalischek , Torben Peters , Jan D. Wegner , Konrad Schindler

Diffusion model based language-guided image editing has achieved great success recently. However, existing state-of-the-art diffusion models struggle with rendering correct text and text style during generation. To tackle this problem, we…

Computer Vision and Pattern Recognition · Computer Science 2023-10-19 Haoxing Chen , Zhuoer Xu , Zhangxuan Gu , Jun Lan , Xing Zheng , Yaohui Li , Changhua Meng , Huijia Zhu , Weiqiang Wang

Despite the ability of existing large-scale text-to-image (T2I) models to generate high-quality images from detailed textual descriptions, they often lack the ability to precisely edit the generated or real images. In this paper, we propose…

Computer Vision and Pattern Recognition · Computer Science 2023-11-21 Chong Mou , Xintao Wang , Jiechong Song , Ying Shan , Jian Zhang

Recent diffusion-based generative models show promise in their ability to generate text images, but limitations in specifying the styles of the generated texts render them insufficient in the realm of typographic design. This paper proposes…

Computer Vision and Pattern Recognition · Computer Science 2024-02-23 KhayTze Peong , Seiichi Uchida , Daichi Haraguchi

Diffusion-based text-to-image models have achieved remarkable results in synthesizing diverse images from text prompts and can capture specific artistic styles via style personalization. However, their entangled latent space and lack of…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Jaehyun Lee , Wonhark Park , Wonsik Shin , Hyunho Lee , Hyoung Min Na , Nojun Kwak

Handwriting of Chinese has long been an important skill in East Asia. However, automatic generation of handwritten Chinese characters poses a great challenge due to the large number of characters. Various machine learning techniques have…

Computer Vision and Pattern Recognition · Computer Science 2018-07-24 Bo Chang , Qiong Zhang , Shenyi Pan , Lili Meng

Few-shot Chinese font generation aims to synthesize new characters in a target style using only a handful of reference images. Achieving accurate content rendering and faithful style transfer requires effective disentanglement between…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Jie Li , Suorong Yang , Jian Zhao , Furao Shen

This paper proposed a method to imitate handwriting style by style transfer. We proposed an neural network model based on conditional generative adversarial networks (cGAN) for handwriting style transfer. This paper improved the loss…

Computer Vision and Pattern Recognition · Computer Science 2022-04-01 Kai Yang , Xiaoman Liang , Huihuang Zhao

Deep generative models have advanced text-to-online handwriting generation (TOHG), which aims to synthesize realistic pen trajectories conditioned on textual input and style references. However, most existing methods still primarily focus…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Wei Pan , Huiguo He , Hiuyi Cheng , Yilin Shi , Lianwen Jin

With the incredible results achieved from generative pre-trained transformers (GPT) and diffusion models, generative AI (GenAI) is envisioned to yield remarkable breakthroughs in various industrial and academic domains. In this paper, we…

Information Theory · Computer Science 2023-09-19 Mehdi Letafati , Samad Ali , Matti Latva-aho

In this work, we propose MetaScript, a novel Chinese content generation system designed to address the diminishing presence of personal handwriting styles in the digital representation of Chinese characters. Our approach harnesses the power…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Xiangyuan Xue , Kailing Wang , Jiazi Bu , Qirui Li , Zhiyuan Zhang

Due to the high complexity and technical requirements of industrial production processes, surface defects will inevitably appear, which seriously affects the quality of products. Although existing lightweight detection networks are highly…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Xuyi Yu