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Text-guided image manipulation with diffusion models enables flexible and precise editing based on prompts, but raises ethical and copyright concerns due to potential unauthorized modifications. To address this, we propose SecureT2I, a…

Cryptography and Security · Computer Science 2025-07-08 Xiaodong Wu , Xiangman Li , Qi Li , Jianbing Ni , Rongxing Lu

Text-to-Image (T2I) models have gained widespread adoption across various applications. Despite the success, the potential misuse of T2I models poses significant risks of generating Not-Safe-For-Work (NSFW) content. To investigate the…

Cryptography and Security · Computer Science 2025-08-07 Xinqi Lyu , Yihao Liu , Yanjie Li , Bin Xiao

Text-to-Image (T2I) models have raised security concerns due to their potential to generate inappropriate or harmful images. In this paper, we propose UPAM, a novel framework that investigates the robustness of T2I models from the attack…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Duo Peng , Qiuhong Ke , Jun Liu

In recent years, fueled by the rapid advancement of diffusion models, text-to-video (T2V) generation models have achieved remarkable progress, with notable examples including Pika, Luma, Kling, and Open-Sora. Although these models exhibit…

Computer Vision and Pattern Recognition · Computer Science 2025-06-18 Jiayang Liu , Siyuan Liang , Shiqian Zhao , Rongcheng Tu , Wenbo Zhou , Aishan Liu , Dacheng Tao , Siew Kei Lam

The rapid advancement of generative AI highlights the importance of text-to-image (T2I) security, particularly with the threat of backdoor poisoning. Timely disclosure and mitigation of security vulnerabilities in T2I models are crucial for…

Cryptography and Security · Computer Science 2025-04-22 Chongye Guo , Jinhu Fu , Junfeng Fang , Kun Wang , Guorui Feng

Diffusion models for Text-to-Image (T2I) conditional generation have recently achieved tremendous success. Yet, aligning these models with user's intentions still involves a laborious trial-and-error process, and this challenging alignment…

Machine Learning · Computer Science 2025-02-12 Chao Wang , Giulio Franzese , Alessandro Finamore , Massimo Gallo , Pietro Michiardi

Recent text-to-image (T2I) models have benefited from large-scale and high-quality data, demonstrating impressive performance. However, these T2I models still struggle to produce images that are aesthetically pleasing, geometrically…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Jianshu Guo , Wenhao Chai , Jie Deng , Hsiang-Wei Huang , Tian Ye , Yichen Xu , Jiawei Zhang , Jenq-Neng Hwang , Gaoang Wang

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…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Zongsheng Cao , Yangfan He , Anran Liu , Jun Xie , Feng Chen , Zepeng Wang

Recent studies have demonstrated the efficacy of integrating Group Relative Policy Optimization (GRPO) into flow matching models, particularly for text-to-image and text-to-video generation. However, we find that directly applying these…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Jin Wang , Jianxiang Lu , Guangzheng Xu , Comi Chen , Haoyu Yang , Linqing Wang , Peng Chen , Mingtao Chen , Zhichao Hu , Longhuang Wu , Shuai Shao , Qinglin Lu , Ping Luo

Text-to-image (T2I) models can generate not-safe-for-work (NSFW) content, motivating multi-stage safety pipelines with both text and image filters. Newer LLM-based filters detect latent intent beyond keywords, making token-level…

Machine Learning · Computer Science 2026-05-26 Zixuan Chen , Hao Lin , Ke Xu , Xinghao Jiang , Tanfeng Sun

Text-to-Image (T2I) diffusion models enable high quality open ended synthesis, but practical use requires suppressing unsafe generations while preserving behavior on benign prompts. We study this tension relative to the frozen generator,…

Artificial Intelligence · Computer Science 2026-05-14 Minhyuk Lee , Hyekyung Yoon , Myungjoo Kang

Text-to-image (T2I) models, though exhibiting remarkable creativity in image generation, can be exploited to produce unsafe images. Existing safety measures, e.g., content moderation or model alignment, fail in the presence of white-box…

Cryptography and Security · Computer Science 2025-10-21 Xinfeng Li , Shengyuan Pang , Jialin Wu , Jiangyi Deng , Huanlong Zhong , Yanjiao Chen , Jie Zhang , Wenyuan Xu

Current text-to-image (T2I) synthesis diffusion models raise misuse concerns, particularly in creating prohibited or not-safe-for-work (NSFW) images. To address this, various safety mechanisms and red teaming attack methods are proposed to…

Cryptography and Security · Computer Science 2025-02-07 Pucheng Dang , Xing Hu , Dong Li , Rui Zhang , Qi Guo , Kaidi Xu

As Text-to-Image (T2I) generation becomes widespread, third-party platforms increasingly integrate multiple model APIs for convenient image creation. However, false claims of using official models can mislead users and harm model owners'…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Zidong Zhao , Yihao Huang , Qing Guo , Tianlin Li , Anran Li , Kailong Wang , Jin Song Dong , Geguang Pu

Text-to-image (T2I) models have advanced creative content generation, yet their reliance on large uncurated datasets often reproduces societal biases. We present FairT2I, a training-free and interactive framework grounded in a…

Computer Vision and Pattern Recognition · Computer Science 2026-01-08 Jinya Sakurai , Yuki Koyama , Issei Sato

The rapid proliferation of AI-Generated Images (AIGIs) has introduced severe risks of misinformation, making AIGI detection a critical yet challenging task. While traditional detection paradigms mainly rely on low-level features, recent…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Chenyang Zhu , Maorong Wang , Jun Liu , Ching-Chun Chang , Isao Echizen

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

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

Text-to-image (T2I) models have been widely applied in generating high-fidelity images across various domains. However, these models may also be abused to produce Not-Safe-for-Work (NSFW) content via jailbreak attacks. Existing jailbreak…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Xingkai Peng , Jun Jiang , Meng Tong , Shuai Li , Weiming Zhang , Nenghai Yu , Kejiang 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