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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 (T2I) models, such as Stable Diffusion, have exhibited remarkable performance in generating high-quality images from text descriptions in recent years. However, text-to-image models may be tricked into generating…

计算机视觉与模式识别 · 计算机科学 2024-10-18 Xinfeng Li , Yuchen Yang , Jiangyi Deng , Chen Yan , Yanjiao Chen , Xiaoyu Ji , Wenyuan Xu

Despite their remarkable image generation capabilities, text-to-image diffusion models inadvertently learn inappropriate concepts from vast and unfiltered training data, which leads to various ethical and business risks. Specifically,…

计算机视觉与模式识别 · 计算机科学 2025-02-18 Die Chen , Zhiwen Li , Mingyuan Fan , Cen Chen , Wenmeng Zhou , Yanhao Wang , Yaliang Li

State-of-the-art Text-to-Image models like Stable Diffusion and DALLE$\cdot$2 are revolutionizing how people generate visual content. At the same time, society has serious concerns about how adversaries can exploit such models to generate…

计算机视觉与模式识别 · 计算机科学 2023-08-17 Yiting Qu , Xinyue Shen , Xinlei He , Michael Backes , Savvas Zannettou , Yang Zhang

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

Text-to-image models are increasingly popular and impactful, yet concerns regarding their safety and fairness remain. This study investigates the ability of ten popular Stable Diffusion models to generate harmful images, including NSFW,…

计算机与社会 · 计算机科学 2025-08-29 Matthias Schneider , Thilo Hagendorff

Text-to-image diffusion models have gained widespread application across various domains, demonstrating remarkable creative potential. However, the strong generalization capabilities of diffusion models can inadvertently lead to the…

计算机视觉与模式识别 · 计算机科学 2025-10-24 Die Chen , Zhiwen Li , Cen Chen , Yuexiang Xie , Xiaodan Li , Jinyan Ye , Yingda Chen , Yaliang 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

The rise of deep learning models in the digital era has raised substantial concerns regarding the generation of Not-Safe-for-Work (NSFW) content. Existing defense methods primarily involve model fine-tuning and post-hoc content moderation.…

计算机视觉与模式识别 · 计算机科学 2025-01-14 Xin Zhao , Xiaojun Chen , Yuexin Xuan , Zhendong Zhao , Xiaojun Jia , Xinfeng Li , Xiaofeng Wang

Score-based generative models (SBM), also known as diffusion models, are the de facto state of the art for image synthesis. Despite their unparalleled performance, SBMs have recently been in the spotlight for being tricked into creating…

计算机视觉与模式识别 · 计算机科学 2025-05-15 Camilo Carvajal Reyes , Joaquín Fontbona , Felipe Tobar

The remarkable ability of diffusion models to generate high-fidelity images has led to their widespread adoption. However, concerns have also arisen regarding their potential to produce Not Safe for Work (NSFW) content and exhibit social…

计算与语言 · 计算机科学 2025-05-22 Zhiwen Li , Die Chen , Mingyuan Fan , Cen Chen , Yaliang Li , Yanhao Wang , Wenmeng Zhou

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-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

The recent advances in diffusion models (DMs) have revolutionized the generation of realistic and complex images. However, these models also introduce potential safety hazards, such as producing harmful content and infringing data…

计算机视觉与模式识别 · 计算机科学 2024-07-09 Yimeng Zhang , Jinghan Jia , Xin Chen , Aochuan Chen , Yihua Zhang , Jiancheng Liu , Ke Ding , Sijia Liu

Text-to-image generative models such as Stable Diffusion and DALL$\cdot$E raise many ethical concerns due to the generation of harmful images such as Not-Safe-for-Work (NSFW) ones. To address these ethical concerns, safety filters are often…

机器学习 · 计算机科学 2023-11-14 Yuchen Yang , Bo Hui , Haolin Yuan , Neil Gong , Yinzhi Cao

Text-to-image (T2I) diffusion models have gained widespread application across various domains, demonstrating remarkable creative potential. However, the strong generalization capabilities of these models can inadvertently led they to…

计算机视觉与模式识别 · 计算机科学 2025-02-19 Die Chen , Zhiwen Li , Cen Chen , Xiaodan Li , Jinyan Ye

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 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

Not Safe/Suitable for Work (NSFW) content is rampant on social networks and poses serious harm to citizens, especially minors. Current detection methods mainly rely on deep learning-based image recognition and classification. However, NSFW…

计算机视觉与模式识别 · 计算机科学 2025-05-30 Han Bao , Qinying Wang , Zhi Chen , Qingming Li , Xuhong Zhang , Changjiang Li , Zonghui Wang , Shouling Ji , Wenzhi Chen

Malicious or manipulated prompts are known to exploit text-to-image models to generate unsafe images. Existing studies, however, focus on the passive exploitation of such harmful capabilities. In this paper, we investigate the proactive…

密码学与安全 · 计算机科学 2025-02-06 Yixin Wu , Ning Yu , Michael Backes , Yun Shen , Yang Zhang
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