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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

Recent advances in large-scale text-to-image (T2I) diffusion models have enabled a variety of downstream applications, including style customization, subject-driven personalization, and conditional generation. As T2I models require…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Zilan Wang , Junfeng Guo , Jiacheng Zhu , Yiming Li , Heng Huang , Muhao Chen , Zhengzhong Tu

Text-to-Image (T2I) models have advanced significantly, but their growing popularity raises security concerns due to their potential to generate harmful images. To address these issues, we propose UPAM, a novel framework to evaluate the…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Duo Peng , Qiuhong Ke , Mark He Huang , Ping Hu , Jun Liu

Recent progress in text-to-image (TTI) systems, such as StableDiffusion, Imagen, and DALL-E 2, have made it possible to create realistic images with simple text prompts. It is tempting to use these systems to eliminate the manual task of…

Computer Vision and Pattern Recognition · Computer Science 2023-11-02 David Marwood , Shumeet Baluja , Yair Alon

Text-to-image (T2I) diffusion models have achieved widespread success due to their ability to generate high-resolution, photorealistic images. These models are trained on large-scale datasets, like LAION-5B, often scraped from the internet.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-04 Korada Sri Vardhana , Shrikrishna Lolla , Soma Biswas

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

As text-to-image models grow increasingly powerful and complex, their burgeoning size presents a significant obstacle to widespread adoption, especially on resource-constrained devices. This paper presents a pioneering study on…

Computer Vision and Pattern Recognition · Computer Science 2024-11-25 Samarth N Ramesh , Zhixue Zhao

Text-to-image (T2I) models have demonstrated remarkable generative capabilities but remain vulnerable to producing not-safe-for-work (NSFW) content, such as violent or explicit imagery. While recent moderation efforts have introduced soft…

Computer Vision and Pattern Recognition · Computer Science 2025-08-15 Zonglei Jing , Xiao Yang , Xiaoqian Li , Siyuan Liang , Aishan Liu , Mingchuan Zhang , Xianglong Liu

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

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

Recently, text-to-image models have been thriving. Despite their powerful generative capacity, our research has uncovered a lack of robustness in this generation process. Specifically, the introduction of small perturbations to the text…

Computer Vision and Pattern Recognition · Computer Science 2023-06-07 Chengbin Du , Yanxi Li , Zhongwei Qiu , Chang Xu

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-to-image (T2I) models are increasingly popular, producing a large share of AI-generated images online. To compare model quality, voting-based leaderboards have become the standard, relying on anonymized model outputs for fairness. In…

Computer Vision and Pattern Recognition · Computer Science 2026-01-15 Ali Naseh , Yuefeng Peng , Anshuman Suri , Harsh Chaudhari , Alina Oprea , Amir Houmansadr

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 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

Text-to-image diffusion models (DMs) have achieved remarkable success in image generation. However, concerns about data privacy and intellectual property remain due to their potential to inadvertently memorize and replicate training data.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Antoni Kowalczuk , Dominik Hintersdorf , Lukas Struppek , Kristian Kersting , Adam Dziedzic , Franziska Boenisch

While recent advancements in generative modeling have significantly improved text-image alignment, some residual misalignment between text and image representations still remains. Some approaches address this issue by fine-tuning models in…

Computer Vision and Pattern Recognition · Computer Science 2025-12-11 Jaa-Yeon Lee , Byunghee Cha , Jeongsol Kim , Jong Chul Ye

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

Text-to-Image (T2I) models have recently achieved remarkable success in generating images from textual descriptions. However, challenges still persist in accurately rendering complex scenes where actions and interactions form the primary…

Computer Vision and Pattern Recognition · Computer Science 2025-09-22 Vatsal Malaviya , Agneet Chatterjee , Maitreya Patel , Yezhou Yang , Chitta Baral

While modern text-to-image (T2I) models excel at generating images from intricate prompts, they struggle to capture the key details when the inputs are descriptive paragraphs. This limitation stems from the prevalence of concise captions…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Jen-Yuan Huang , Tong Lin , Yilun Du