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Recent developments in text-to-image models, particularly Stable Diffusion, have marked significant achievements in various applications. With these advancements, there are growing safety concerns about the vulnerability of the model that…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Chenyu Zhang , Lanjun Wang , Anan Liu

Text-to-Image (T2I) generation methods based on diffusion model have garnered significant attention in the last few years. Although these image synthesis methods produce visually appealing results, they frequently exhibit spelling errors…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Yiming Zhao , Zhouhui Lian

Despite the impressive generative capabilities of text-to-image (T2I) diffusion models, they remain vulnerable to generating inappropriate content, especially when confronted with implicit sexual prompts. Unlike explicit harmful prompts,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Yitong Sun , Yao Huang , Ruochen Zhang , Huanran Chen , Shouwei Ruan , Ranjie Duan , Xingxing Wei

Large-scale text-to-image (T2I) diffusion models have revolutionized image generation, enabling the synthesis of highly detailed visuals from textual descriptions. However, these models may inadvertently generate inappropriate content, such…

Computer Vision and Pattern Recognition · Computer Science 2025-03-24 Huiqiang Chen , Tianqing Zhu , Linlin Wang , Xin Yu , Longxiang Gao , Wanlei Zhou

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

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…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Yimeng Zhang , Jinghan Jia , Xin Chen , Aochuan Chen , Yihua Zhang , Jiancheng Liu , Ke Ding , Sijia Liu

Text-to-image (T2I) diffusion models have shown exceptional capabilities in generating images that closely correspond to textual prompts. However, the advancement of T2I diffusion models presents significant risks, as the models could be…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Jie Ren , Kangrui Chen , Yingqian Cui , Shenglai Zeng , Hui Liu , Yue Xing , Jiliang Tang , Lingjuan Lyu

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

Text-conditioned image generation models have recently achieved astonishing results in image quality and text alignment and are consequently employed in a fast-growing number of applications. Since they are highly data-driven, relying on…

Computer Vision and Pattern Recognition · Computer Science 2023-04-27 Patrick Schramowski , Manuel Brack , Björn Deiseroth , Kristian Kersting

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

Despite the notable advancements and versatility of multi-modal diffusion models, such as text-to-image models, their susceptibility to adversarial inputs remains underexplored. Contrary to expectations, our investigations reveal that the…

Computer Vision and Pattern Recognition · Computer Science 2025-10-31 Xiaosen Wang , Zhijin Ge , Shaokang Wang

Text-to-image diffusion models, e.g. Stable Diffusion (SD), lately have shown remarkable ability in high-quality content generation, and become one of the representatives for the recent wave of transformative AI. Nevertheless, such advance…

Computation and Language · Computer Science 2026-01-15 Zhi-Yi Chin , Chieh-Ming Jiang , Ching-Chun Huang , Pin-Yu Chen , Wei-Chen Chiu

Large-scale image generation models, with impressive quality made possible by the vast amount of data available on the Internet, raise social concerns that these models may generate harmful or copyrighted content. The biases and harmfulness…

Computer Vision and Pattern Recognition · Computer Science 2023-07-13 Sanghyun Kim , Seohyeon Jung , Balhae Kim , Moonseok Choi , Jinwoo Shin , Juho Lee

With advances in diffusion models, image generation has shown significant performance improvements. This raises concerns about the potential abuse of image generation, such as the creation of explicit or violent images, commonly referred to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Junha Park , Jaehui Hwang , Ian Ryu , Hyungkeun Park , Jiyoon Kim , Jong-Seok Lee

There is growing concern over the safety of powerful diffusion models (DMs), as they are often misused to produce inappropriate, not-safe-for-work (NSFW) content or generate copyrighted material or data of individuals who wish to be…

Artificial Intelligence · Computer Science 2026-02-24 Mingyu Kim , Dongjun Kim , Amman Yusuf , Stefano Ermon , Mijung Park

In the rapidly advancing realm of visual generation, diffusion models have revolutionized the landscape, marking a significant shift in capabilities with their impressive text-guided generative functions. However, relying solely on text for…

Computer Vision and Pattern Recognition · Computer Science 2026-01-09 Pu Cao , Feng Zhou , Qing Song , Lu Yang

Diffusion models have emerged as a dominant paradigm for generative modeling across a wide range of domains, including prompt-conditional generation. The vast majority of samplers, however, rely on forward discretization of the reverse…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Zhenghan Fang , Jian Zheng , Qiaozi Gao , Xiaofeng Gao , Jeremias Sulam

Large-scale Text-to-Image (T2I) diffusion models demonstrate significant generation capabilities based on textual prompts. Based on the T2I diffusion models, text-guided image editing research aims to empower users to manipulate generated…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Chuanming Tang , Kai Wang , Fei Yang , Joost van de Weijer

Text-to-image (T2I) research has grown explosively in the past year, owing to the large-scale pre-trained diffusion models and many emerging personalization and editing approaches. Yet, one pain point persists: the text prompt engineering,…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Xingqian Xu , Jiayi Guo , Zhangyang Wang , Gao Huang , Irfan Essa , Humphrey Shi

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