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Related papers: Evaluating the Robustness of Text-to-image Diffusi…

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Text-to-image diffusion models (T2I DMs) have achieved remarkable success in generating high-quality and diverse images from text prompts, yet recent studies have revealed their vulnerability to backdoor attacks. Existing attack methods…

Cryptography and Security · Computer Science 2025-08-05 Haoran Dai , Jiawen Wang , Ruo Yang , Manali Sharma , Zhonghao Liao , Yuan Hong , Binghui Wang

Text-to-Image (T2I) Diffusion Models (DMs) have garnered widespread attention for their impressive advancements in image generation. However, their growing popularity has raised ethical and social concerns related to key non-functional…

Machine Learning · Computer Science 2025-07-22 Yi Zhang , Zhen Chen , Chih-Hong Cheng , Wenjie Ruan , Xiaowei Huang , Dezong Zhao , David Flynn , Siddartha Khastgir , Xingyu Zhao

Text-to-Image (T2I) Diffusion Models (DMs) have shown impressive abilities in generating high-quality images based on simple text descriptions. However, as is common with many Deep Learning (DL) models, DMs are subject to a lack of…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Yi Zhang , Yun Tang , Wenjie Ruan , Xiaowei Huang , Siddartha Khastgir , Paul Jennings , Xingyu Zhao

Text-to-image diffusion models have been widely adopted in real-world applications due to their ability to generate realistic images from textual descriptions. However, recent studies have shown that these methods are vulnerable to backdoor…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Oscar Chew , Po-Yi Lu , Jayden Lin , Hsuan-Tien Lin

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

In recent years, Text-to-Image (T2I) models have seen remarkable advancements, gaining widespread adoption. However, this progress has inadvertently opened avenues for potential misuse, particularly in generating inappropriate or…

Cryptography and Security · Computer Science 2024-04-02 Yijun Yang , Ruiyuan Gao , Xiaosen Wang , Tsung-Yi Ho , Nan Xu , Qiang Xu

Recently, the text-to-image diffusion model has gained considerable attention from the community due to its exceptional image generation capability. A representative model, Stable Diffusion, amassed more than 10 million users within just…

Cryptography and Security · Computer Science 2024-09-16 Chenyu Zhang , Mingwang Hu , Wenhui Li , Lanjun Wang

With the help of conditioning mechanisms, the state-of-the-art diffusion models have achieved tremendous success in guided image generation, particularly in text-to-image synthesis. To gain a better understanding of the training process and…

Cryptography and Security · Computer Science 2023-10-24 Shengfang Zhai , Yinpeng Dong , Qingni Shen , Shi Pu , Yuejian Fang , Hang Su

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

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 (T2I) models such as Stable Diffusion have advanced rapidly and are now widely used in content creation. However, these models can be misused to generate harmful content, including nudity or violence, posing significant safety…

Cryptography and Security · Computer Science 2025-06-13 Zilong Wang , Xiang Zheng , Xiaosen Wang , Bo Wang , Xingjun Ma , Yu-Gang Jiang

Diffusion models (DMs) have achieved state-of-the-art performance on various generative tasks such as image synthesis, text-to-image, and text-guided image-to-image generation. However, the more powerful the DMs, the more harmful they…

Cryptography and Security · Computer Science 2024-08-08 Vu Tuan Truong , Luan Ba Dang , Long Bao Le

While language models have made many milestones in text inference and classification tasks, they remain susceptible to adversarial attacks that can lead to unforeseen outcomes. Existing works alleviate this problem by equipping language…

Computation and Language · Computer Science 2024-01-10 Shilong Yuan , Wei Yuan , Hongzhi Yin , Tieke He

Despite the record-breaking performance in Text-to-Image (T2I) generation by Stable Diffusion, less research attention is paid to its adversarial robustness. In this work, we study the problem of adversarial attack generation for Stable…

Computer Vision and Pattern Recognition · Computer Science 2023-04-04 Haomin Zhuang , Yihua Zhang , Sijia Liu

Diffusion models (DMs) have demonstrated great potential in the field of adversarial robustness, where DM-based defense methods can achieve superior defense capability without adversarial training. However, they all require huge…

Computer Vision and Pattern Recognition · Computer Science 2025-02-12 Hefei Mei , Minjing Dong , Chang Xu

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

Latent diffusion models achieve state-of-the-art performance on a variety of generative tasks, such as image synthesis and image editing. However, the robustness of latent diffusion models is not well studied. Previous works only focus on…

Computer Vision and Pattern Recognition · Computer Science 2023-06-16 Jianping Zhang , Zhuoer Xu , Shiwen Cui , Changhua Meng , Weibin Wu , Michael R. Lyu

Advances in diffusion-based video generation models, while significantly improving human animation, poses threats of misuse through the creation of fake videos from a specific person's photo and text prompts. Recent efforts have focused on…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Duc Vu , Anh Nguyen , Chi Tran , Anh Tran

The popularization of Text-to-Image (T2I) diffusion models enables the generation of high-quality images from text descriptions. However, generating diverse customized images with reference visual attributes remains challenging. This work…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Brian Nlong Zhao , Yuhang Xiao , Jiashu Xu , Xinyang Jiang , Yifan Yang , Dongsheng Li , Laurent Itti , Vibhav Vineet , Yunhao Ge

Text-to-Image (T2I) diffusion models have rapidly advanced, enabling the generation of high-quality images that align closely with textual descriptions. However, this progress has also raised concerns about their misuse for propaganda and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-25 Jaechul Roh , Andrew Yuan , Jinsong Mao
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