English
Related papers

Related papers: HTS-Attack: Heuristic Token Search for Jailbreakin…

200 papers

Human motion generation driven by deep generative models has enabled compelling applications, but the ability of text-to-motion (T2M) models to produce realistic motions from text prompts raises security concerns if exploited maliciously.…

Computer Vision and Pattern Recognition · Computer Science 2024-08-02 Honglei Miao , Fan Ma , Ruijie Quan , Kun Zhan , Yi Yang

Recent advances in Text-to-Image (T2I) generative models, such as Imagen, Stable Diffusion, and FLUX, have led to remarkable improvements in visual quality. However, their performance is fundamentally limited by the quality of training…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Kaixin Ding , Yang Zhou , Xi Chen , Miao Yang , Jiarong Ou , Rui Chen , Xin Tao , Hengshuang Zhao

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…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Yu Xie , Chengjie Zeng , Lingyun Zhang , Yanwei Fu

Recent text-to-image (T2I) diffusion models show outstanding performance in generating high-quality images conditioned on textual prompts. However, they fail to semantically align the generated images with the prompts due to their limited…

Computer Vision and Pattern Recognition · Computer Science 2023-12-15 Ruichen Wang , Zekang Chen , Chen Chen , Jian Ma , Haonan Lu , Xiaodong Lin

Text-to-image models have shown remarkable capabilities in generating high-quality images from natural language descriptions. However, these models are highly vulnerable to adversarial prompts, which can bypass safety measures and produce…

Cryptography and Security · Computer Science 2025-10-16 Peigui Qi , Kunsheng Tang , Wenbo Zhou , Weiming Zhang , Nenghai Yu , Tianwei Zhang , Qing Guo , Jie Zhang

Text-to-Image (T2I) models, represented by DALL$\cdot$E and Midjourney, have gained huge popularity for creating realistic images. The quality of these images relies on the carefully engineered prompts, which have become valuable…

Cryptography and Security · Computer Science 2026-01-22 Shiqian Zhao , Chong Wang , Yiming Li , Yihao Huang , Wenjie Qu , Siew-Kei Lam , Yi Xie , Kangjie Chen , Jie Zhang , Tianwei Zhang

Text-to-Image (T2I) models have made remarkable progress in generating high-quality, diverse visual content from natural language prompts. However, their ability to reproduce copyrighted styles, sensitive imagery, and harmful content raises…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Changhoon Kim , Yanjun Qi

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…

Computer Vision and Pattern Recognition · Computer Science 2024-10-18 Xinfeng Li , Yuchen Yang , Jiangyi Deng , Chen Yan , Yanjiao Chen , Xiaoyu Ji , Wenyuan Xu

Person re-identification (ReID) aims to retrieve target pedestrian images given either visual queries (image-to-image, I2I) or textual descriptions (text-to-image, T2I). Although both tasks share a common retrieval objective, they pose…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Linhan Zhou , Shuang Li , Neng Dong , Yonghang Tai , Yafei Zhang , Huafeng Li

Text-to-Image (T2I) models have made remarkable progress in generating images from text prompts, but their output quality and safety still depend heavily on how prompts are phrased. Existing safety methods typically refine prompts using…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Jinwoo Jeon , JunHyeok Oh , Hayeong Lee , Byung-Jun Lee

Despite advancements in text-to-image generation (T2I), prior methods often face text-image misalignment problems such as relation confusion in generated images. Existing solutions involve cross-attention manipulation for better…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Leigang Qu , Wenjie Wang , Yongqi Li , Hanwang Zhang , Liqiang Nie , Tat-Seng Chua

Current large language models (LLM) provide a strong foundation for large-scale user-oriented natural language tasks. Many users can easily inject adversarial text or instructions through the user interface, thus causing LLM model security…

Computation and Language · Computer Science 2024-11-14 Chong Zhang , Mingyu Jin , Dong Shu , Taowen Wang , Dongfang Liu , Xiaobo Jin

Vision-Language Models (VLMs) are increasingly susceptible to sophisticated adversarial attacks, including adaptive strategies specifically designed to bypass existing defenses. To address this vulnerability, we propose MirrorCheck, a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Samar Fares , Klea Ziu , Toluwani Aremu , Nikita Durasov , Martin Takáč , Pascal Fua , Ivan Laptev , Karthik Nandakumar

Text-to-image synthesis (T2I) aims to generate photo-realistic images which are semantically consistent with the text descriptions. Existing methods are usually built upon conditional generative adversarial networks (GANs) and initialize an…

Computer Vision and Pattern Recognition · Computer Science 2022-03-25 Kai Hu , Wentong Liao , Michael Ying Yang , Bodo Rosenhahn

Natural language processing models based on neural networks are vulnerable to adversarial examples. These adversarial examples are imperceptible to human readers but can mislead models to make the wrong predictions. In a black-box setting,…

Computation and Language · Computer Science 2023-03-14 Hai Zhu , Qingyang Zhao , Yuren Wu

Recent text-to-video (T2V) models can synthesize complex videos from lightweight natural language prompts, raising urgent concerns about safety alignment in the event of misuse in the real world. Prior jailbreak attacks typically rewrite…

Cryptography and Security · Computer Science 2026-03-10 Moyang Chen , Zonghao Ying , Wenzhuo Xu , Quancheng Zou , Deyue Zhang , Dongdong Yang , Xiangzheng Zhang

Contemporary Text-to-Image (T2I) models frequently depend on qualitative human evaluations to assess the consistency between synthesized images and the text prompts. There is a demand for quantitative and automatic evaluation tools, given…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Ziyuan Qin , Dongjie Cheng , Haoyu Wang , Huahui Yi , Yuting Shao , Zhiyuan Fan , Kang Li , Qicheng Lao

Text-to-Image (T2I) models have made significant advancements in recent years, but they still struggle to accurately capture intricate details specified in complex compositional prompts. While fine-tuning T2I models with reward objectives…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Luca Eyring , Shyamgopal Karthik , Karsten Roth , Alexey Dosovitskiy , Zeynep Akata

Significant progress has been achieved in subject-driven text-to-image (T2I) generation, which aims to synthesize new images depicting target subjects according to user instructions. However, evaluating these models remains a significant…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Zhenyu Hu , Qing Wang , Te Cao , Luo Liao , Longfei Lu , Liqun Liu , Shuang Li , Hang Chen , Mengge Xue , Yuan Chen , Chao Deng , Peng Shu , Huan Yu , Jie Jiang

Large Language Models (LLMs) have demonstrated exceptional performance across various tasks, but their security vulnerabilities can be exploited by attackers to generate harmful content, causing adverse impacts across various societal…

Cryptography and Security · Computer Science 2025-12-17 Fan Yang
‹ Prev 1 4 5 6 7 8 10 Next ›