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Recent text-to-image (T2I) models have had great success, and many benchmarks have been proposed to evaluate their performance and safety. However, they only consider explicit prompts while neglecting implicit prompts (hint at a target…

Computers and Society · Computer Science 2024-05-29 Yue Yang , Yuqi Lin , Hong Liu , Wenqi Shao , Runjian Chen , Hailong Shang , Yu Wang , Yu Qiao , Kaipeng Zhang , Ping Luo

Text-to-image generation models~(e.g., Stable Diffusion) have achieved significant advancements, enabling the creation of high-quality and realistic images based on textual descriptions. Prompt inversion, the task of identifying the textual…

Computer Vision and Pattern Recognition · Computer Science 2026-03-06 Mingzhe Li , Kejing Xia , Gehao Zhang , Zhenting Wang , Guanhong Tao , Siqi Pan , Juan Zhai , Shiqing Ma

TIPO (Text-to-Image Prompt Optimization) introduces an efficient approach for automatic prompt refinement in text-to-image (T2I) generation. Starting from simple user prompts, TIPO leverages a lightweight pre-trained model to expand these…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Shih-Ying Yeh , Yi Li , Sang-Hyun Park , Giyeong Oh , Xuehai Wang , Min Song , Youngjae Yu , Shang-Hong Lai

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 models have shown remarkable progress in generating high-quality images from user-provided prompts. Despite this, the quality of these images varies due to the models' sensitivity to human language nuances. With advancements…

Artificial Intelligence · Computer Science 2024-06-14 Xinrui Yang , Zhuohan Wang , Anthony Hu

Recently, the strong latent Diffusion Probabilistic Model (DPM) has been applied to high-quality Text-to-Image (T2I) generation (e.g., Stable Diffusion), by injecting the encoded target text prompt into the gradually denoised diffusion…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Mingyang Yi , Aoxue Li , Yi Xin , Zhenguo Li

Text-to-image (T2I) diffusion models have drawn attention for their ability to generate high-quality images with precise text alignment. However, these models can also be misused to produce inappropriate content. Existing safety measures,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Hongxiang Zhang , Yifeng He , Hao Chen

Text-to-image generative models, specifically those based on diffusion models like Imagen and Stable Diffusion, have made substantial advancements. Recently, there has been a surge of interest in the delicate refinement of text prompts.…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Wenyi Mo , Tianyu Zhang , Yalong Bai , Bing Su , Ji-Rong Wen , Qing Yang

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

Clinical trials are essential to drug development but time-consuming, costly, and prone to failure. Accurate trial outcome prediction based on historical trial data promises better trial investment decisions and more trial success. Existing…

Machine Learning · Computer Science 2023-04-12 Zifeng Wang , Cao Xiao , Jimeng Sun

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 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

Diffusion models excel in many generative modeling tasks, notably in creating images from text prompts, a task referred to as text-to-image (T2I) generation. Despite the ability to generate high-quality images, these models often replicate…

Multimedia · Computer Science 2024-02-20 Yang Zhang , Teoh Tze Tzun , Lim Wei Hern , Haonan Wang , Kenji Kawaguchi

In recent years, text-to-image (T2I) generation models have made significant progress in generating high-quality images that align with text descriptions. However, these models also face the risk of unsafe generation, potentially producing…

Cryptography and Security · Computer Science 2025-04-16 Huming Qiu , Guanxu Chen , Mi Zhang , Xiaohan Zhang , Xiaoyu You , Min Yang

Despite their impressive capabilities, diffusion-based text-to-image (T2I) models can lack faithfulness to the text prompt, where generated images may not contain all the mentioned objects, attributes or relations. To alleviate these…

Computer Vision and Pattern Recognition · Computer Science 2023-05-23 Shyamgopal Karthik , Karsten Roth , Massimiliano Mancini , Zeynep Akata

Despite the impressive synthesis quality of text-to-image (T2I) diffusion models, their black-box deployment poses significant regulatory challenges: Malicious actors can fine-tune these models to generate illegal content, circumventing…

Computer Vision and Pattern Recognition · Computer Science 2025-03-31 Zhuomeng Zhang , Fangqi Li , Chong Di , Hongyu Zhu , Hanyi Wang , Shilin Wang

Although recent text-to-image (T2I) diffusion models excel at aligning generated images with textual prompts, controlling the visual style of the output remains a challenging task. In this work, we propose Style-Prompting Guidance (SPG), a…

Graphics · Computer Science 2025-08-18 Qian Liang , Zichong Chen , Yang Zhou , Hui Huang

Diffusion-based text-to-image (T2I) models enable high-quality image generation but also pose significant risks of misuse, particularly in producing not-safe-for-work (NSFW) content. While prior detection methods have focused on filtering…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Fan Yang , Yihao Huang , Jiayi Zhu , Ling Shi , Geguang Pu , Jin Song Dong , Kailong Wang

Compositional text-to-image (T2I) generation requires a model to honour multiple sub-prompts that describe distinct image regions. Recent work shows that the \emph{starting noise} of a diffusion model carries significant semantic…

Computer Vision and Pattern Recognition · Computer Science 2026-04-29 Hao Li

Recently, diffusion models have made remarkable progress in text-to-image (T2I) generation, synthesizing images with high fidelity and diverse contents. Despite this advancement, latent space smoothness within diffusion models remains…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Jiayi Guo , Xingqian Xu , Yifan Pu , Zanlin Ni , Chaofei Wang , Manushree Vasu , Shiji Song , Gao Huang , Humphrey Shi