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Diffusion model based Text-to-Image has achieved impressive achievements recently. Although current technology for synthesizing images is highly advanced and capable of generating images with high fidelity, it is still possible to give the…

Computer Vision and Pattern Recognition · Computer Science 2024-02-22 Yuxiang Tuo , Wangmeng Xiang , Jun-Yan He , Yifeng Geng , Xuansong Xie

This work demonstrates that diffusion models can achieve font-controllable multilingual text rendering using just raw images without font label annotations.Visual text rendering remains a significant challenge. While recent methods…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Bowen Jiang , Yuan Yuan , Xinyi Bai , Zhuoqun Hao , Alyson Yin , Yaojie Hu , Wenyu Liao , Lyle Ungar , Camillo J. Taylor

Diffusion models, known for their impressive image generation abilities, have played a pivotal role in the rise of visual text generation. Nevertheless, existing visual text generation methods often focus on generating entire images with…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Zhenhang Li , Yan Shu , Weichao Zeng , Dongbao Yang , Yu Zhou

Plain text has become a prevalent interface for text-to-image synthesis. However, its limited customization options hinder users from accurately describing desired outputs. For example, plain text makes it hard to specify continuous…

Computer Vision and Pattern Recognition · Computer Science 2025-01-16 Songwei Ge , Taesung Park , Jun-Yan Zhu , Jia-Bin Huang

Recent text-to-image diffusion models are able to generate convincing results of unprecedented quality. However, it is nearly impossible to control the shapes of different regions/objects or their layout in a fine-grained fashion. Previous…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Omri Avrahami , Thomas Hayes , Oran Gafni , Sonal Gupta , Yaniv Taigman , Devi Parikh , Dani Lischinski , Ohad Fried , Xi Yin

Scene text recognition in low-resource languages frequently faces challenges due to the limited availability of training datasets derived from real-world scenes. This study proposes a novel approach that generates text images in…

Computer Vision and Pattern Recognition · Computer Science 2024-09-27 Chihiro Noguchi , Shun Fukuda , Shoichiro Mihara , Masao Yamanaka

Evaluating text-to-image generative models remains a challenge, despite the remarkable progress being made in their overall performances. While existing metrics like CLIPScore work for coarse evaluations, they lack the sensitivity to…

Computer Vision and Pattern Recognition · Computer Science 2024-11-06 Georgia Gabriela Sampaio , Ruixiang Zhang , Shuangfei Zhai , Jiatao Gu , Josh Susskind , Navdeep Jaitly , Yizhe Zhang

Text-to-image generation has greatly advanced content creation, yet accurately rendering visual text remains a key challenge due to blurred glyphs, semantic drift, and limited style control. Existing methods often rely on pre-rendered glyph…

Computer Vision and Pattern Recognition · Computer Science 2025-07-03 Yuanrui Wang , Cong Han , Yafei Li , Zhipeng Jin , Xiawei Li , SiNan Du , Wen Tao , Yi Yang , Shuanglong Li , Chun Yuan , Liu Lin

Textual image generation spans diverse fields like advertising, education, product packaging, social media, information visualization, and branding. Despite recent strides in language-guided image synthesis using diffusion models, current…

Computer Vision and Pattern Recognition · Computer Science 2024-05-22 Shubham Paliwal , Arushi Jain , Monika Sharma , Vikram Jamwal , Lovekesh Vig

Recent breakthroughs in the field of language-guided image generation have yielded impressive achievements, enabling the creation of high-quality and diverse images based on user instructions.Although the synthesis performance is…

Computer Vision and Pattern Recognition · Computer Science 2023-05-24 Jian Ma , Mingjun Zhao , Chen Chen , Ruichen Wang , Di Niu , Haonan Lu , Xiaodong Lin

Recently, diffusion-based image generation methods are credited for their remarkable text-to-image generation capabilities, while still facing challenges in accurately generating multilingual scene text images. To tackle this problem, we…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Lingjun Zhang , Xinyuan Chen , Yaohui Wang , Yue Lu , Yu Qiao

While recent text-to-image models can generate photorealistic images from text prompts that reflect detailed instructions, they still face significant challenges in accurately rendering words in the image. In this paper, we propose to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-01 Wataru Shimoda , Naoto Inoue , Daichi Haraguchi , Hayato Mitani , Seiichi Uchida , Kota Yamaguchi

Real-world text image super-resolution aims to restore overall visual quality and text legibility in images suffering from diverse degradations and text distortions. However, the scarcity of text image data in existing datasets results in…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Haodong He , Xin Zhan , Yancheng Bai , Rui Lan , Lei Sun , Xiangxiang Chu

Scene text synthesis involves rendering specified texts onto arbitrary images. Current methods typically formulate this task in an end-to-end manner but lack effective character-level guidance during training. Besides, their text encoders,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Yibin Wang , Weizhong Zhang , Honghui Xu , Cheng Jin

Text-to-image diffusion models have demonstrated tremendous success in synthesizing visually stunning images given textual instructions. Despite remarkable progress in creating high-fidelity visuals, text-to-image models can still struggle…

Computer Vision and Pattern Recognition · Computer Science 2025-12-15 Taewook Kim , Ze Wang , Zhengyuan Yang , Jiang Wang , Lijuan Wang , Zicheng Liu , Qiang Qiu

While diffusion models have significantly advanced the quality of image generation their capability to accurately and coherently render text within these images remains a substantial challenge. Conventional diffusion-based methods for scene…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Qilong Zhangli , Jindong Jiang , Di Liu , Licheng Yu , Xiaoliang Dai , Ankit Ramchandani , Guan Pang , Dimitris N. Metaxas , Praveen Krishnan

As the text-to-image (T2I) domain progresses, generating text that seamlessly integrates with visual content has garnered significant attention. However, even with accurate text generation, the inability to control font and color can…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Yuxiang Tuo , Yifeng Geng , Liefeng Bo

We introduce the first method, to the best of our knowledge, for adapting image-to-video models to layer-aware text (glyph) animation, a capability critical for practical dynamic visual design. Existing approaches predominantly handle the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Fei Zhang , Zijian Zhou , Bohao Tang , Sen He , Hang Li , Zhe Wang , Soubhik Sanyal , Pengfei Liu , Viktar Atliha , Tao Xiang , Frost Xu , Semih Gunel

Recent advances in text-to-image diffusion models have enabled the photorealistic generation of images from text prompts. Despite the great progress, existing models still struggle to generate compositional multi-concept images naturally,…

Computer Vision and Pattern Recognition · Computer Science 2023-10-12 Hazarapet Tunanyan , Dejia Xu , Shant Navasardyan , Zhangyang Wang , Humphrey Shi

Restoring low-resolution text images presents a significant challenge, as it requires maintaining both the fidelity and stylistic realism of the text in restored images. Existing text image restoration methods often fall short in hard…

Computer Vision and Pattern Recognition · Computer Science 2025-06-17 Chenglu Pan , Xiaogang Xu , Ganggui Ding , Yunke Zhang , Wenbo Li , Jiarong Xu , Qingbiao Wu
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