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In recent years, Text-to-Image (T2I) models have been extensively studied, especially with the emergence of diffusion models that achieve state-of-the-art results on T2I synthesis tasks. However, existing benchmarks heavily rely on…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Eslam Mohamed Bakr , Pengzhan Sun , Xiaoqian Shen , Faizan Farooq Khan , Li Erran Li , Mohamed Elhoseiny

The rapid development of generative artificial intelligence has made text to video models essential for building future multimodal world simulators. However, these models remain vulnerable to jailbreak attacks, where specially crafted…

Cryptography and Security · Computer Science 2025-04-29 Siyuan Liang , Jiayang Liu , Jiecheng Zhai , Tianmeng Fang , Rongcheng Tu , Aishan Liu , Xiaochun Cao , Dacheng Tao

Text-to-Image models may generate harmful content, such as pornographic images, particularly when unsafe prompts are submitted. To address this issue, safety filters are often added on top of text-to-image models, or the models themselves…

Cryptography and Security · Computer Science 2026-01-09 Zhengyuan Jiang , Yuepeng Hu , Yuchen Yang , Yinzhi Cao , Neil Zhenqiang Gong

Text-to-image (T2I) models such as Stable Diffusion and DALLE remain susceptible to generating harmful or Not-Safe-For-Work (NSFW) content under jailbreak attacks despite deployed safety filters. Existing jailbreak attacks either rely on…

Computer Vision and Pattern Recognition · Computer Science 2026-03-27 Haolun Zheng , Yu He , Tailun Chen , Shuo Shao , Zhixuan Chu , Hongbin Zhou , Lan Tao , Zhan Qin , Kui Ren

While text-to-image diffusion models demonstrate impressive generation capabilities, they also exhibit vulnerability to backdoor attacks, which involve the manipulation of model outputs through malicious triggers. In this paper, for the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Zhongqi Wang , Jie Zhang , Shiguang Shan , Xilin Chen

Text-to-image (T2I) models commonly incorporate defense mechanisms to prevent the generation of sensitive images. Unfortunately, recent jailbreak attacks have shown that adversarial prompts can effectively bypass these mechanisms and induce…

Cryptography and Security · Computer Science 2026-03-25 Chenyu Zhang , Lanjun Wang , Yiwen Ma , Wenhui Li , Yi Tu , An-An Liu

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…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Chi Zhang , Changjia Zhu , Xiaowen Li , Yao Liu , Zhuo Lu

While deep learning based image retrieval is reported to be vulnerable to adversarial attacks, existing works are mainly on image-to-image retrieval with their attacks performed at the front end via query modification. By contrast, we…

Multimedia · Computer Science 2023-03-14 Fan Hu , Aozhu Chen , Xirong Li

The rapid evolution of text-to-image (T2I) models has enabled high-fidelity visual synthesis on a global scale. However, these advancements have introduced significant security risks, particularly regarding the generation of harmful…

Cryptography and Security · Computer Science 2026-01-16 Wonwoo Choi , Minjae Seo , Minkyoo Song , Hwanjo Heo , Seungwon Shin , Myoungsung You

Recently, various types of Text-to-Image (T2I) models have emerged (such as DALL-E and Stable Diffusion), and showing their advantages in different aspects. Therefore, some third-party service platforms collect different model interfaces…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Ji Guo , Wenbo Jiang , Rui Zhang , Guoming Lu , Hongwei Li

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…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Muhammad Shahid Muneer , Simon S. Woo

Diffusion models have recently achieved remarkable advancements in terms of image quality and fidelity to textual prompts. Concurrently, the safety of such generative models has become an area of growing concern. This work introduces a…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Tong Liu , Zhixin Lai , Jiawen Wang , Gengyuan Zhang , Shuo Chen , Philip Torr , Vera Demberg , Volker Tresp , Jindong Gu

In recent years, Text-to-Image (T2I) models have garnered significant attention due to their remarkable advancements. However, security concerns have emerged due to their potential to generate inappropriate or Not-Safe-For-Work (NSFW)…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Yihao Huang , Le Liang , Tianlin Li , Xiaojun Jia , Run Wang , Weikai Miao , Geguang Pu , Yang Liu

Although recent personalization methods have democratized high-resolution image synthesis by enabling swift concept acquisition with minimal examples and lightweight computation, they also present an exploitable avenue for high accessible…

Computer Vision and Pattern Recognition · Computer Science 2023-12-21 Yihao Huang , Felix Juefei-Xu , Qing Guo , Jie Zhang , Yutong Wu , Ming Hu , Tianlin Li , Geguang Pu , Yang Liu

Text-to-image generative models are widely deployed in creative tools and online platforms. To mitigate misuse, these systems rely on safety filters and moderation pipelines that aim to block harmful or policy violating content. In this…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Ahmed B Mustafa , Zihan Ye , Yang Lu , Michael P Pound , Shreyank N Gowda

Current text-to-image (T2I) generation models achieve promising results, but they fail on the scenarios where the knowledge implied in the text prompt is uncertain. For example, a T2I model released in February would struggle to generate a…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Chuanhao Li , Jianwen Sun , Yukang Feng , Mingliang Zhai , Yifan Chang , Kaipeng Zhang

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

Text-to-Image (T2I) diffusion models have demonstrated strong generation ability, but their potential to generate unsafe content raises significant safety concerns. Existing inference-time defense methods typically perform category-agnostic…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Binhong Tan , Zhaoxin Wang , Handing Wang

The development of text-to-image (T2I) generative models, that enable the creation of high-quality synthetic images from textual prompts, has opened new frontiers in creative design and content generation. However, this paper reveals a…

Computer Vision and Pattern Recognition · Computer Science 2025-01-23 Zonglei Jing , Zonghao Ying , Le Wang , Siyuan Liang , Aishan Liu , Xianglong Liu , Dacheng Tao

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…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Jiangweizhi Peng , Zhiwei Tang , Gaowen Liu , Charles Fleming , Mingyi Hong