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

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Contents generated by recent advanced Text-to-Image (T2I) diffusion models are sometimes too imaginative for existing off-the-shelf dense predictors to estimate due to the immitigable domain gap. We introduce DMP, a pipeline utilizing…

Computer Vision and Pattern Recognition · Computer Science 2024-04-04 Hsin-Ying Lee , Hung-Yu Tseng , Hsin-Ying Lee , Ming-Hsuan Yang

In this paper, we present an empirical study introducing a nuanced evaluation framework for text-to-image (T2I) generative models, applied to human image synthesis. Our framework categorizes evaluations into two distinct groups: first,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Muxi Chen , Yi Liu , Jian Yi , Changran Xu , Qiuxia Lai , Hongliang Wang , Tsung-Yi Ho , Qiang Xu

Text-to-Image (T2I) generation models have been widely adopted across various industries, yet are criticized for frequently exhibiting societal stereotypes. While a growing body of research has emerged to evaluate and mitigate these biases,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Megan Smith , Venkatesh Thirugnana Sambandham , Florian Richter , Laura Crompton , Matthias Uhl , Torsten Schön

Personalized text-to-image models allow users to generate varied styles of images (specified with a sentence) for an object (specified with a set of reference images). While remarkable results have been achieved using diffusion-based…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Fanyue Wei , Wei Zeng , Zhenyang Li , Dawei Yin , Lixin Duan , Wen Li

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

Latent diffusion models (LDMs) achieve state-of-the-art performance across various tasks, including image generation and video synthesis. However, they generally lack robustness, a limitation that remains not fully explored in current…

Machine Learning · Computer Science 2025-06-10 Boris Martirosyan , Alexey Karmanov

The rapid evolution of Text-to-Video (T2V) diffusion models has driven remarkable advancements in generating high-quality, temporally coherent videos from natural language descriptions. Despite these achievements, their vulnerability to…

Computer Vision and Pattern Recognition · Computer Science 2026-01-01 Changzhen Li , Yuecong Min , Jie Zhang , Zheng Yuan , Shiguang Shan , Xilin Chen

As recent advances in large-scale Text-to-Image (T2I) diffusion models have yielded remarkable high-quality image generation, diverse downstream Image-to-Image (I2I) applications have emerged. Despite the impressive results achieved by…

Computer Vision and Pattern Recognition · Computer Science 2024-10-11 Geonung Kim , Beomsu Kim , Eunhyeok Park , Sunghyun Cho

Recent advances in diffusion models have significantly enhanced the quality of image synthesis, yet they have also introduced serious safety concerns, particularly the generation of Not Safe for Work (NSFW) content. Previous research has…

Computer Vision and Pattern Recognition · Computer Science 2025-09-15 Yaopei Zeng , Yuanpu Cao , Bochuan Cao , Yurui Chang , Jinghui Chen , Lu Lin

Text-to-image diffusion models are nothing but a revolution, allowing anyone, even without design skills, to create realistic images from simple text inputs. With powerful personalization tools like DreamBooth, they can generate images of a…

Computer Vision and Pattern Recognition · Computer Science 2023-10-23 Thanh Van Le , Hao Phung , Thuan Hoang Nguyen , Quan Dao , Ngoc Tran , Anh Tran

Recent advancements in Text-to-Image (T2I) models have raised significant safety concerns about their potential misuse for generating inappropriate or Not-Safe-For-Work (NSFW) contents, despite existing countermeasures such as NSFW…

Computer Vision and Pattern Recognition · Computer Science 2024-10-31 Yijun Yang , Ruiyuan Gao , Xiao Yang , Jianyuan Zhong , Qiang Xu

Text-to-image (T2I) generative models have gained increased popularity in the public domain. While boasting impressive user-guided generative abilities, their black-box nature exposes users to intentionally- and intrinsically-biased…

Computer Vision and Pattern Recognition · Computer Science 2024-09-18 Jordan Vice , Naveed Akhtar , Richard Hartley , Ajmal Mian

Cutting-edge works have demonstrated that text-to-image (T2I) diffusion models can generate adversarial patches that mislead state-of-the-art object detectors in the physical world, revealing detectors' vulnerabilities and risks. However,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Wenjun Ji , Yuxiang Fu , Luyang Ying , Deng-Ping Fan , Yuyi Wang , Ming-Ming Cheng , Ivor Tsang , Qing Guo

Text-to-image diffusion models, such as Stable Diffusion, have shown exceptional potential in generating high-quality images. However, recent studies highlight concerns over the use of unauthorized data in training these models, which may…

Computer Vision and Pattern Recognition · Computer Science 2024-11-28 Soumil Datta , Shih-Chieh Dai , Leo Yu , Guanhong Tao

Text-to-Image (T2I) models have recently gained significant attention due to their ability to generate high-quality images and are consequently used in a wide range of applications. However, there are concerns about the gender bias of these…

Computer Vision and Pattern Recognition · Computer Science 2025-07-28 Yunbo Lyu , Zhou Yang , Yuqing Niu , Jing Jiang , David Lo

Applying diffusion models to image-to-image translation (I2I) has recently received increasing attention due to its practical applications. Previous attempts inject information from the source image into each denoising step for an iterative…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Mengfei Xia , Yu Zhou , Ran Yi , Yong-Jin Liu , Wenping Wang

Evaluating the quality of automatically generated image descriptions is a complex task that requires metrics capturing various dimensions, such as grammaticality, coverage, accuracy, and truthfulness. Although human evaluation provides…

Computer Vision and Pattern Recognition · Computer Science 2024-11-11 Jia-Hong Huang , Hongyi Zhu , Yixian Shen , Stevan Rudinac , Evangelos Kanoulas

Recent advancements in text-to-image (T2I) generative models have shown remarkable capabilities in producing diverse and imaginative visuals based on text prompts. Despite the advancement, these diffusion models sometimes struggle to…

Computer Vision and Pattern Recognition · Computer Science 2023-11-30 Xiaohui Chen , Yongfei Liu , Yingxiang Yang , Jianbo Yuan , Quanzeng You , Li-Ping Liu , Hongxia Yang

Text-to-image generation (TTI) refers to the usage of models that could process text input and generate high fidelity images based on text descriptions. Text-to-image generation using neural networks could be traced back to the emergence of…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Fengxiang Bie , Yibo Yang , Zhongzhu Zhou , Adam Ghanem , Minjia Zhang , Zhewei Yao , Xiaoxia Wu , Connor Holmes , Pareesa Golnari , David A. Clifton , Yuxiong He , Dacheng Tao , Shuaiwen Leon Song

Modern text-to-image (T2I) models can now render legible, paragraph-length text, enabling a fundamentally new class of misuse. We identify and formalize the inscriptive jailbreak, where an adversary coerces a T2I system into generating…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Zonghao Ying , Haowen Dai , Lianyu Hu , Zonglei Jing , Quanchen Zou , Yaodong Yang , Aishan Liu , Xianglong Liu
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