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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

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

Text-to-image models have shown remarkable capabilities in generating high-quality images from natural language descriptions. However, these models are highly vulnerable to adversarial prompts, which can bypass safety measures and produce…

密码学与安全 · 计算机科学 2025-10-16 Peigui Qi , Kunsheng Tang , Wenbo Zhou , Weiming Zhang , Nenghai Yu , Tianwei Zhang , Qing Guo , Jie Zhang

Recent text-to-image (T2I) models have exhibited remarkable performance in generating high-quality images from text descriptions. However, these models are vulnerable to misuse, particularly generating not-safe-for-work (NSFW) content, such…

计算机视觉与模式识别 · 计算机科学 2026-05-12 Lingzhi Yuan , Xinfeng Li , Chejian Xu , Guanhong Tao , Xiaojun Jia , Yihao Huang , Wei Dong , Yang Liu , Bo Li

The rapid advancement of text-to-image (T2I) models, such as Stable Diffusion, has enhanced their capability to synthesize images from textual prompts. However, this progress also raises significant risks of misuse, including the generation…

计算机视觉与模式识别 · 计算机科学 2025-06-24 Yu Xie , Chengjie Zeng , Lingyun Zhang , Yanwei Fu

In the past years, we have witnessed the remarkable success of Text-to-Image (T2I) models and their widespread use on the web. Extensive research in making T2I models produce hyper-realistic images has led to new concerns, such as…

计算机视觉与模式识别 · 计算机科学 2025-04-17 Muhammad Shahid Muneer , Simon S. Woo

State-of-the-art Diffusion Models (DMs) produce highly realistic images. While prior work has successfully mitigated Not Safe For Work (NSFW) content in the visual domain, we identify a novel threat: the generation of NSFW text embedded…

计算机视觉与模式识别 · 计算机科学 2026-01-16 Aditya Kumar , Tom Blanchard , Adam Dziedzic , Franziska Boenisch

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

Generative Artificial Intelligence (AI) has created unprecedented opportunities for creative expression, education, and research. Text-to-image systems such as DALL.E, Stable Diffusion, and Midjourney can now convert ideas into visuals…

人工智能 · 计算机科学 2025-12-16 Dang Phuong Nam , Nguyen Kieu , Pham Thanh Hieu

Text-to-image (T2I) models have significantly advanced in producing high-quality images. However, such models have the ability to generate images containing not-safe-for-work (NSFW) content, such as pornography, violence, political content,…

密码学与安全 · 计算机科学 2025-05-15 Longtian Wang , Xiaofei Xie , Tianlin Li , Yuhan Zhi , Chao Shen

Text-to-image models can generate harmful images when presented with unsafe prompts, posing significant safety and societal risks. Alignment methods aim to modify these models to ensure they generate only non-harmful images, even when…

密码学与安全 · 计算机科学 2025-03-03 Yuepeng Hu , Zhengyuan Jiang , Neil Zhenqiang Gong

Text-to-Image (T2I) generation is a popular AI-generated content (AIGC) technology enabling diverse and creative image synthesis. However, some outputs may contain Not Safe For Work (NSFW) content (e.g., violence), violating community…

计算机视觉与模式识别 · 计算机科学 2026-01-21 Mingrui Liu , Sixiao Zhang , Cheng Long

Recent advances in diffusion models have notably enhanced text-to-image (T2I) generation quality, but they also raise the risk of generating unsafe content. Traditional safety methods like text blacklisting or harmful content classification…

计算机视觉与模式识别 · 计算机科学 2025-12-30 Zongsheng Cao , Yangfan He , Anran Liu , Jun Xie , Feng Chen , Zepeng Wang

Diffusion-based text-to-image (T2I) models enable high-quality image generation but also pose significant risks of misuse, particularly in producing not-safe-for-work (NSFW) content. While prior detection methods have focused on filtering…

计算机视觉与模式识别 · 计算机科学 2025-08-06 Fan Yang , Yihao Huang , Jiayi Zhu , Ling Shi , Geguang Pu , Jin Song Dong , Kailong Wang

Text-to-Image (T2I) diffusion models are widely recognized for their ability to generate high-quality and diverse images based on text prompts. However, despite recent advances, these models are still prone to generating unsafe images…

计算机视觉与模式识别 · 计算机科学 2024-12-06 Jiangweizhi Peng , Zhiwei Tang , Gaowen Liu , Charles Fleming , Mingyi Hong

With the ability to generate high-quality images, text-to-image (T2I) models can be exploited for creating inappropriate content. To prevent misuse, existing safety measures are either based on text blacklists, which can be easily…

计算机视觉与模式识别 · 计算机科学 2024-08-20 Runtao Liu , Ashkan Khakzar , Jindong Gu , Qifeng Chen , Philip Torr , Fabio Pizzati

Recent advancements in Text-to-Image (T2I) models have raised significant safety concerns about their potential misuse for generating inappropriate or Not-Safe-For-Work (NSFW) contents, despite existing countermeasures such as NSFW…

计算机视觉与模式识别 · 计算机科学 2024-10-31 Yijun Yang , Ruiyuan Gao , Xiao Yang , Jianyuan Zhong , Qiang Xu

Recent advances in diffusion models have significantly enhanced the quality of image synthesis, yet they have also introduced serious safety concerns, particularly the generation of Not Safe for Work (NSFW) content. Previous research has…

计算机视觉与模式识别 · 计算机科学 2025-09-15 Yaopei Zeng , Yuanpu Cao , Bochuan Cao , Yurui Chang , Jinghui Chen , Lu Lin

Text-to-image (T2I) generation has made remarkable progress in producing high-quality images, but a fundamental challenge remains: creating backgrounds that naturally accommodate text placement without compromising image quality. This…

计算机视觉与模式识别 · 计算机科学 2025-05-14 Tianyi Liang , Jiangqi Liu , Yifei Huang , Shiqi Jiang , Jianshen Shi , Changbo Wang , Chenhui Li

Text-to-image (T2I) models have demonstrated remarkable generative capabilities but remain vulnerable to producing not-safe-for-work (NSFW) content, such as violent or explicit imagery. While recent moderation efforts have introduced soft…

计算机视觉与模式识别 · 计算机科学 2025-08-15 Zonglei Jing , Xiao Yang , Xiaoqian Li , Siyuan Liang , Aishan Liu , Mingchuan Zhang , Xianglong Liu
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