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The rapid advancement of diffusion models has enabled high-fidelity and semantically rich text-to-image generation; however, ensuring fairness and safety remains an open challenge. Existing methods typically improve fairness and safety at…

计算机视觉与模式识别 · 计算机科学 2025-10-09 Silpa Vadakkeeveetil Sreelatha , Sauradip Nag , Muhammad Awais , Serge Belongie , Anjan Dutta

The incredible generative ability of large-scale text-to-image (T2I) models has demonstrated strong power of learning complex structures and meaningful semantics. However, relying solely on text prompts cannot fully take advantage of the…

计算机视觉与模式识别 · 计算机科学 2023-03-21 Chong Mou , Xintao Wang , Liangbin Xie , Yanze Wu , Jian Zhang , Zhongang Qi , Ying Shan , Xiaohu Qie

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…

计算机视觉与模式识别 · 计算机科学 2025-05-27 Jordan Vice , Naveed Akhtar , Leonid Sigal , Richard Hartley , Ajmal Mian

Text-to-image (T2I) generation aims to synthesize images from textual prompts, which jointly specify what must be shown and imply what can be inferred, which thus correspond to two core capabilities: \textbf{\textit{composition}} and…

计算机视觉与模式识别 · 计算机科学 2026-03-03 Ouxiang Li , Yuan Wang , Xinting Hu , Huijuan Huang , Rui Chen , Jiarong Ou , Xin Tao , Pengfei Wan , Xiaojuan Qi , Fuli Feng

Large-scale text-to-image diffusion models have been a revolutionary milestone in the evolution of generative AI and multimodal technology, allowing wonderful image generation with natural-language text prompt. However, the issue of lacking…

计算机视觉与模式识别 · 计算机科学 2025-11-18 Xiang Gao , Jiaying Liu

This paper analyzes the community safety guidelines of five text-to-image (T2I) generation platforms and audits five T2I models, focusing on prompts related to the representation of humans in areas that might lead to societal stigma. While…

计算机与社会 · 计算机科学 2024-09-27 Piera Riccio , Georgina Curto , Nuria Oliver

Generative models, particularly diffusion-based text-to-image (T2I) models, have demonstrated astounding success. However, aligning them to avoid generating content with unacceptable concepts (e.g., offensive or copyrighted content, or…

计算机视觉与模式识别 · 计算机科学 2025-06-11 Anudeep Das , Gurjot Singh , Prach Chantasantitam , N. Asokan

Large-scale text-to-image generative models have been a revolutionary breakthrough in the evolution of generative AI, allowing us to synthesize diverse images that convey highly complex visual concepts. However, a pivotal challenge in…

计算机视觉与模式识别 · 计算机科学 2022-11-24 Narek Tumanyan , Michal Geyer , Shai Bagon , Tali Dekel

Text-to-Image (T2I) models have demonstrated impressive capabilities in generating high-quality and diverse visual content from natural language prompts. However, uncontrolled reproduction of sensitive, copyrighted, or harmful imagery poses…

计算机视觉与模式识别 · 计算机科学 2025-05-30 Yiwei Xie , Ping Liu , Zheng Zhang

Text-and-Image-To-Image (TI2I), an extension of Text-To-Image (T2I), integrates image inputs with textual instructions to enhance image generation. Existing methods often partially utilize image inputs, focusing on specific elements like…

计算机视觉与模式识别 · 计算机科学 2025-03-20 Teng-Fang Hsiao , Bo-Kai Ruan , Yi-Lun Wu , Tzu-Ling Lin , Hong-Han Shuai

In recent years, text-to-image (T2I) generation models have made significant progress in generating high-quality images that align with text descriptions. However, these models also face the risk of unsafe generation, potentially producing…

密码学与安全 · 计算机科学 2025-04-16 Huming Qiu , Guanxu Chen , Mi Zhang , Xiaohan Zhang , Xiaoyu You , Min Yang

Text-to-Image (T2I) generation models have been widely adopted across various industries, yet are criticized for frequently exhibiting societal stereotypes. While a growing body of research has emerged to evaluate and mitigate these biases,…

计算机视觉与模式识别 · 计算机科学 2026-04-21 Megan Smith , Venkatesh Thirugnana Sambandham , Florian Richter , Laura Crompton , Matthias Uhl , Torsten Schön

Diffusion-based models have gained significant popularity for text-to-image generation due to their exceptional image-generation capabilities. A risk with these models is the potential generation of inappropriate content, such as biased or…

计算机视觉与模式识别 · 计算机科学 2024-03-29 Hang Li , Chengzhi Shen , Philip Torr , Volker Tresp , Jindong Gu

Text-to-Image (T2I) models have made remarkable progress in generating high-quality, diverse visual content from natural language prompts. However, their ability to reproduce copyrighted styles, sensitive imagery, and harmful content raises…

计算机视觉与模式识别 · 计算机科学 2025-06-09 Changhoon Kim , Yanjun Qi

In the rapidly advancing realm of visual generation, diffusion models have revolutionized the landscape, marking a significant shift in capabilities with their impressive text-guided generative functions. However, relying solely on text for…

计算机视觉与模式识别 · 计算机科学 2026-01-09 Pu Cao , Feng Zhou , Qing Song , Lu Yang

With the advance of generative AI, the text-to-image (T2I) model has the ability to generate various contents. However, the generated contents cannot be fully controlled. There is a potential risk that T2I model can generate unsafe images…

计算机视觉与模式识别 · 计算机科学 2024-10-10 Dong Han , Salaheldin Mohamed , Yong Li

Diffusion models excel in many generative modeling tasks, notably in creating images from text prompts, a task referred to as text-to-image (T2I) generation. Despite the ability to generate high-quality images, these models often replicate…

多媒体 · 计算机科学 2024-02-20 Yang Zhang , Teoh Tze Tzun , Lim Wei Hern , Haonan Wang , Kenji Kawaguchi

Despite advancements in text-to-image generation (T2I), prior methods often face text-image misalignment problems such as relation confusion in generated images. Existing solutions involve cross-attention manipulation for better…

计算机视觉与模式识别 · 计算机科学 2024-03-15 Leigang Qu , Wenjie Wang , Yongqi Li , Hanwang Zhang , Liqiang Nie , Tat-Seng Chua

Text-to-image (T2I) diffusion models have the ability to build high-quality pictures from text prompts, but they pose safety concerns because they can generate offensive or disturbing imagery when provided with harmful inputs. Existing…

计算机视觉与模式识别 · 计算机科学 2026-05-05 Chi Zhang , Changjia Zhu , Xiaowen Li , Yao Liu , Zhuo Lu

In this paper, we present an empirical study introducing a nuanced evaluation framework for text-to-image (T2I) generative models, applied to human image synthesis. Our framework categorizes evaluations into two distinct groups: first,…

计算机视觉与模式识别 · 计算机科学 2024-10-29 Muxi Chen , Yi Liu , Jian Yi , Changran Xu , Qiuxia Lai , Hongliang Wang , Tsung-Yi Ho , Qiang Xu
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