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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

Text-to-image (T2I) models have emerged as a significant advancement in generative AI; however, there exist safety concerns regarding their potential to produce harmful image outputs even when users input seemingly safe prompts. This…

Computers and Society · Computer Science 2024-08-19 Susan Hao , Renee Shelby , Yuchi Liu , Hansa Srinivasan , Mukul Bhutani , Burcu Karagol Ayan , Ryan Poplin , Shivani Poddar , Sarah Laszlo

This paper presents a community-centered study of cultural limitations of text-to-image (T2I) models in the South Asian context. We theorize these failures using scholarship on dominant media regimes of representations and locate them…

Computers and Society · Computer Science 2024-03-14 Rida Qadri , Renee Shelby , Cynthia L. Bennett , Remi Denton

Text-to-image generative models excel in creating images from text but struggle with ensuring alignment and consistency between outputs and prompts. This paper introduces TextMatch, a novel framework that leverages multimodal optimization…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Yucong Luo , Mingyue Cheng , Jie Ouyang , Xiaoyu Tao , Qi Liu

Advances in generative models have led to significant interest in image synthesis, demonstrating the ability to generate high-quality images for a diverse range of text prompts. Despite this progress, most studies ignore the presence of…

Artificial Intelligence · Computer Science 2024-07-02 Nila Masrourisaadat , Nazanin Sedaghatkish , Fatemeh Sarshartehrani , Edward A. Fox

Text-to-image (T2I) generation has greatly enhanced creative expression, yet achieving preference-aligned generation in a real-time and training-free manner remains challenging. Previous methods often rely on static, pre-collected…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Yang Li , Songlin Yang , Xiaoxuan Han , Wei Wang , Jing Dong , Yueming Lyu , Ziyu Xue

Text-to-image (T2I) generative models have recently emerged as a powerful tool, enabling the creation of photo-realistic images and giving rise to a multitude of applications. However, the effective integration of T2I models into…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Zhicai Wang , Longhui Wei , Tan Wang , Heyu Chen , Yanbin Hao , Xiang Wang , Xiangnan He , Qi Tian

The rapid proliferation of multimodal generative models has sparked critical discussions on their reliability, fairness and potential for misuse. While text-to-image models excel at producing high-fidelity, user-guided content, they often…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Jordan Vice , Naveed Akhtar , Leonid Sigal , Richard Hartley , Ajmal Mian

Text-to-image generative models often reflect the biases of the training data, leading to unequal representations of underrepresented groups. This study investigates inclusive text-to-image generative models that generate images based on…

Computer Vision and Pattern Recognition · Computer Science 2023-09-12 Cheng Zhang , Xuanbai Chen , Siqi Chai , Chen Henry Wu , Dmitry Lagun , Thabo Beeler , Fernando De la Torre

Text-to-image generation models have recently achieved astonishing results in image quality, flexibility, and text alignment, and are consequently employed in a fast-growing number of applications. Through improvements in multilingual…

The steady improvements of text-to-image (T2I) generative models lead to slow deprecation of automatic evaluation benchmarks that rely on static datasets, motivating researchers to seek alternative ways to evaluate the T2I progress. In this…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 Jiahui Chen , Candace Ross , Reyhane Askari-Hemmat , Koustuv Sinha , Melissa Hall , Michal Drozdzal , Adriana Romero-Soriano

Despite advances in generation quality, current text-to-image (T2I) models often lack diversity, generating homogeneous outputs. This work introduces a framework to address the need for robust diversity evaluation in T2I models. Our…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Isabela Albuquerque , Ira Ktena , Olivia Wiles , Ivana Kajić , Amal Rannen-Triki , Cristina Vasconcelos , Aida Nematzadeh

Recent advancements in text-to-image (T2I) generation models have transformed the field. However, challenges persist in generating images that reflect demanding textual descriptions, especially for fine-grained details and unusual…

Multimedia · Computer Science 2025-02-21 Ran Li , Xiaomeng Jin , Heng ji

Reinforcement learning (RL) has garnered increasing attention in text-to-image (T2I) generation. However, most existing RL approaches are tailored to either diffusion models or autoregressive models, overlooking an important alternative:…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Yifu Luo , Xinhao Hu , Keyu Fan , Haoyuan Sun , Zeyu Chen , Bo Xia , Tiantian Zhang , Yongzhe Chang , Xueqian Wang

Text-to-image (T2I) generative models are largely used in AI-powered real-world applications and value creation. However, their strategic deployment raises critical concerns for responsible AI management, particularly regarding the…

Machine Learning · Computer Science 2025-11-18 Abu Sufian , Cosimo Distante , Marco Leo , Hanan Salam

Recent advancements in generative models have significantly enhanced their capacity for image generation, enabling a wide range of applications such as image editing, completion and video editing. A specialized area within generative…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Jiaxin Cheng , Zixu Zhao , Tong He , Tianjun Xiao , Yicong Zhou , Zheng Zhang

Text-to-Image (T2I) models have transformed visual content creation, producing highly realistic images from natural language prompts. However, concerns persist around their potential to replicate and magnify existing societal biases. To…

Computer Vision and Pattern Recognition · Computer Science 2025-06-18 Sedat Porikli , Vedat Porikli

Warning: This paper contains several contents that may be toxic, harmful, or offensive. In the last few years, text-to-image generative models have gained remarkable success in generating images with unprecedented quality accompanied by a…

Computation and Language · Computer Science 2023-06-02 Jialu Wang , Xinyue Gabby Liu , Zonglin Di , Yang Liu , Xin Eric Wang

Text-to-Image (T2I) generative models are becoming increasingly crucial due to their ability to generate high-quality images, but also raise concerns about social biases, particularly in human image generation. Sociological research has…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Hanjun Luo , Haoyu Huang , Ziye Deng , Xinfeng Li , Hewei Wang , Yingbin Jin , Yang Liu , Wenyuan Xu , Zuozhu Liu

Text-to-image (T2I) generative models have gained increased popularity in the public domain. While boasting impressive user-guided generative abilities, their black-box nature exposes users to intentionally- and intrinsically-biased…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Jordan Vice , Naveed Akhtar , Richard Hartley , Ajmal Mian