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This paper explores a novel lightweight approach LightFair to achieve fair text-to-image diffusion models (T2I DMs) by addressing the adverse effects of the text encoder. Most existing methods either couple different parts of the diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Boyu Han , Qianqian Xu , Shilong Bao , Zhiyong Yang , Kangli Zi , Qingming Huang

Accurate color alignment in text-to-image (T2I) generation is critical for applications such as fashion, product visualization, and interior design, yet current diffusion models struggle with nuanced and compound color terms (e.g., Tiffany…

Computer Vision and Pattern Recognition · Computer Science 2025-09-15 Sung-Lin Tsai , Bo-Lun Huang , Yu Ting Shen , Cheng Yu Yeo , Chiang Tseng , Bo-Kai Ruan , Wen-Sheng Lien , Hong-Han Shuai

Recent advancements in Text-to-Image (T2I) diffusion models have demonstrated impressive success in generating high-quality images with zero-shot generalization capabilities. Yet, current models struggle to closely adhere to prompt…

Computer Vision and Pattern Recognition · Computer Science 2024-01-31 Hyun Kang , Dohae Lee , Myungjin Shin , In-Kwon Lee

Image-to-image translation (I2I) transforms an image from a source domain to a target domain while preserving source content. Most computer vision applications are in the field of image-to-image translation, such as style transfer, image…

Image and Video Processing · Electrical Eng. & Systems 2025-02-18 Mehran Safayani , Behnaz Mirzapour , Hanieh aghaebrahimiyan , Nasrin Salehi , Hamid Ravaee

Text-to-image (T2I) diffusion/flow models have drawn considerable attention recently due to their remarkable ability to deliver flexible visual creations. Still, high-resolution image synthesis presents formidable challenges due to the…

Computer Vision and Pattern Recognition · Computer Science 2025-05-19 Jiazi Bu , Pengyang Ling , Yujie Zhou , Pan Zhang , Tong Wu , Xiaoyi Dong , Yuhang Zang , Yuhang Cao , Dahua Lin , Jiaqi Wang

Personalized text-to-image models allow users to generate varied styles of images (specified with a sentence) for an object (specified with a set of reference images). While remarkable results have been achieved using diffusion-based…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Fanyue Wei , Wei Zeng , Zhenyang Li , Dawei Yin , Lixin Duan , Wen Li

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

Large-scale diffusion models have achieved remarkable performance in generative tasks. Beyond their initial training applications, these models have proven their ability to function as versatile plug-and-play priors. For instance, 2D…

Computer Vision and Pattern Recognition · Computer Science 2025-02-21 Xiaofeng Yang , Cheng Chen , Xulei Yang , Fayao Liu , Guosheng Lin

Text-to-image (T2I) models have advanced creative content generation, yet their reliance on large uncurated datasets often reproduces societal biases. We present FairT2I, a training-free and interactive framework grounded in a…

Computer Vision and Pattern Recognition · Computer Science 2026-01-08 Jinya Sakurai , Yuki Koyama , Issei Sato

The proliferation of text-to-image diffusion models (T2I DMs) has led to an increased presence of AI-generated images in daily life. However, biased T2I models can generate content with specific tendencies, potentially influencing people's…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Huayang Huang , Xiangye Jin , Jiaxu Miao , Yu Wu

In this study, we aim to enhance the capabilities of diffusion-based text-to-image (T2I) generation models by integrating diverse modalities beyond textual descriptions within a unified framework. To this end, we categorize widely used…

Computer Vision and Pattern Recognition · Computer Science 2025-08-27 Sungnyun Kim , Junsoo Lee , Kibeom Hong , Daesik Kim , Namhyuk Ahn

Text-to-image (T2I) diffusion models generate high-quality images but often fail to capture the spatial relations specified in text prompts. This limitation can be traced to two factors: lack of fine-grained spatial supervision in training…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Sarah Rastegar , Violeta Chatalbasheva , Sieger Falkena , Anuj Singh , Yanbo Wang , Tejas Gokhale , Hamid Palangi , Hadi Jamali-Rad

In the last two years, text-to-image diffusion models have become extremely popular. As their quality and usage increase, a major concern has been the need for better output control. In addition to prompt engineering, one effective method…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Clément Bonnet , Ariel N. Lee , Franck Wertel , Antoine Tamano , Tanguy Cizain , Pablo Ducru

Text-to-image generation (T2I) refers to the text-guided generation of high-quality images. In the past few years, T2I has attracted widespread attention and numerous works have emerged. In this survey, we comprehensively review 141 works…

Computer Vision and Pattern Recognition · Computer Science 2025-05-06 Pengfei Yang , Ngai-Man Cheung , Xinda Ma

With the rise of large, publicly-available text-to-image diffusion models, text-guided real image editing has garnered much research attention recently. Existing methods tend to either rely on some form of per-instance or per-task…

Computer Vision and Pattern Recognition · Computer Science 2022-11-16 Adham Elarabawy , Harish Kamath , Samuel Denton

Text-to-image (T2I) models have recently experienced rapid development, achieving astonishing performance in terms of fidelity and textual alignment capabilities. However, given a long paragraph (up to 512 words), these generation models…

Computer Vision and Pattern Recognition · Computer Science 2025-05-07 Weijia Wu , Zhuang Li , Yefei He , Mike Zheng Shou , Chunhua Shen , Lele Cheng , Yan Li , Tingting Gao , Di Zhang

Generative modeling is widely regarded as one of the most essential problems in today's AI community, with text-to-image generation having gained unprecedented real-world impacts. Among various approaches, diffusion models have achieved…

Computer Vision and Pattern Recognition · Computer Science 2026-01-26 Xuyang Guo , Jiayan Huo , Yingyu Liang , Zhenmei Shi , Zhao Song , Jiahao Zhang , Zhen Zhuang

With the advent of diffusion models, Text-to-Image (T2I) generation has seen substantial advancements. Current T2I models allow users to specify object colors using linguistic color names, and some methods aim to personalize color-object…

Graphics · Computer Science 2025-08-13 Qianru Qiu , Jiafeng Mao , Xueting Wang

Despite their impressive capabilities, diffusion-based text-to-image (T2I) models can lack faithfulness to the text prompt, where generated images may not contain all the mentioned objects, attributes or relations. To alleviate these…

Computer Vision and Pattern Recognition · Computer Science 2023-05-23 Shyamgopal Karthik , Karsten Roth , Massimiliano Mancini , Zeynep Akata

With the open-sourcing of text-to-image models (T2I) such as stable diffusion (SD) and stable diffusion XL (SD-XL), there is an influx of models fine-tuned in specific domains based on the open-source SD model, such as in anime, character…

Computer Vision and Pattern Recognition · Computer Science 2023-12-20 Ruyi Gan , Xiaojun Wu , Junyu Lu , Yuanhe Tian , Dixiang Zhang , Ziwei Wu , Renliang Sun , Chang Liu , Jiaxing Zhang , Pingjian Zhang , Yan Song
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