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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 this paper, we highlight a critical threat posed by emerging neural models: data plagiarism. We demonstrate how modern neural models (e.g., diffusion models) can replicate copyrighted images, even when protected by advanced watermarking…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Zihang Zou , Boqing Gong , Liqiang Wang

Diffusion models have attracted significant attention due to its exceptional data generation capabilities in fields such as image synthesis. However, recent studies have shown that diffusion models are vulnerable to copyright infringement…

Artificial Intelligence · Computer Science 2025-08-22 Zhixiang Guo , Siyuan Liang , Aishan Liu , Dacheng Tao

The commercialization of text-to-image diffusion models (DMs) brings forth potential copyright concerns. Despite numerous attempts to protect DMs from copyright issues, the vulnerabilities of these solutions are underexplored. In this…

Cryptography and Security · Computer Science 2024-05-28 Haonan Wang , Qianli Shen , Yao Tong , Yang Zhang , Kenji Kawaguchi

Diffusion Models (DMs) have evolved into advanced image generation tools, especially for few-shot generation where a pretrained model is fine-tuned on a small set of images to capture a specific style or object. Despite their success,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Xiaoyu Wu , Yang Hua , Chumeng Liang , Jiaru Zhang , Hao Wang , Tao Song , Haibing Guan

Generative AI has witnessed rapid advancement in recent years, expanding their capabilities to create synthesized content such as text, images, audio, and code. The high fidelity and authenticity of contents generated by these Deep…

Cryptography and Security · Computer Science 2024-07-25 Jie Ren , Han Xu , Pengfei He , Yingqian Cui , Shenglai Zeng , Jiankun Zhang , Hongzhi Wen , Jiayuan Ding , Pei Huang , Lingjuan Lyu , Hui Liu , Yi Chang , Jiliang Tang

Copyright law confers upon creators the exclusive rights to reproduce, distribute, and monetize their creative works. However, recent progress in text-to-image generation has introduced formidable challenges to copyright enforcement. These…

Computer Vision and Pattern Recognition · Computer Science 2024-06-24 Rui Ma , Qiang Zhou , Yizhu Jin , Daquan Zhou , Bangjun Xiao , Xiuyu Li , Yi Qu , Aishani Singh , Kurt Keutzer , Jingtong Hu , Xiaodong Xie , Zhen Dong , Shanghang Zhang , Shiji Zhou

The widespread deployment of large vision models such as Stable Diffusion raises significant legal and ethical concerns, as these models can memorize and reproduce copyrighted content without authorization. Existing detection approaches…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Xiafeng Man , Zhipeng Wei , Jingjing Chen

Web-based AI image generation has become an innovative art form that can generate novel artworks with the rapid development of the diffusion model. However, this new technique brings potential copyright infringement risks as it may…

Computer Vision and Pattern Recognition · Computer Science 2023-11-23 Junlei Zhou , Jiashi Gao , Ziwei Wang , Xuetao Wei

Recent progress in diffusion models has profoundly enhanced the fidelity of image generation, but it has raised concerns about copyright infringements. While prior methods have introduced adversarial perturbations to prevent style…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Namhyuk Ahn , Wonhyuk Ahn , KiYoon Yoo , Daesik Kim , Seung-Hun Nam

The proliferation of diffusion models trained on web-scale, provenance-uncertain image collections has made it essential, yet technically unresolved, to determine whether a model has learned from specific copyrighted data without…

Machine Learning · Computer Science 2026-04-06 Muxing Li , Zesheng Ye , Sharon Li , Andy Song , Guangquan Zhang , Feng Liu

Recent text-to-image generative models such as Stable Diffusion are extremely adept at mimicking and generating copyrighted content, raising concerns amongst artists that their unique styles may be improperly copied. Understanding how…

Computer Vision and Pattern Recognition · Computer Science 2024-04-15 Mazda Moayeri , Samyadeep Basu , Sriram Balasubramanian , Priyatham Kattakinda , Atoosa Chengini , Robert Brauneis , Soheil Feizi

Structural information in images is crucial for aesthetic assessment, and it is widely recognized in the artistic field that imitating the structure of other works significantly infringes on creators' rights. The advancement of diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-02-12 Chuanwei Huang , Zexi Jia , Hongyan Fei , Yeshuang Zhu , Zhiqiang Yuan , Jinchao Zhang , Jie Zhou

Recent proliferation of generative AI tools for visual content creation-particularly in the context of visual artworks-has raised serious concerns about copyright infringement and forgery. The large-scale datasets used to train these models…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 Haroon Wahab , Hassan Ugail , Irfan Mehmood

Generative AI models, renowned for their ability to synthesize high-quality content, have sparked growing concerns over the improper generation of copyright-protected material. While recent studies have proposed various approaches to…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Qipan Xu , Zhenting Wang , Xiaoxiao He , Ligong Han , Ruixiang Tang

Recent text-to-image diffusion models have shown surprising performance in generating high-quality images. However, concerns have arisen regarding the unauthorized data usage during the training or fine-tuning process. One example is when a…

Computer Vision and Pattern Recognition · Computer Science 2024-04-10 Zhenting Wang , Chen Chen , Lingjuan Lyu , Dimitris N. Metaxas , Shiqing Ma

Video recognition systems are increasingly being deployed in daily life, such as content recommendation and security monitoring. To enhance video recognition development, many institutions have released high-quality public datasets with…

Cryptography and Security · Computer Science 2025-12-17 Quan Yuan , Zhikun Zhang , Linkang Du , Min Chen , Mingyang Sun , Yunjun Gao , Shibo He , Jiming Chen

Assessing whether AI-generated images are substantially similar to source works is a crucial step in resolving copyright disputes. In this paper, we propose CopyJudge, a novel automated infringement identification framework that leverages…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Shunchang Liu , Zhuan Shi , Lingjuan Lyu , Yaochu Jin , Boi Faltings

As generative artificial intelligence technologies like Stable Diffusion advance, visual content becomes more vulnerable to misuse, raising concerns about copyright infringement. Visual watermarks serve as effective protection mechanisms,…

Computer Vision and Pattern Recognition · Computer Science 2025-05-19 Junxian Duan , Jiyang Guan , Wenkui Yang , Ran He

Visual diffusion models have revolutionized the field of creative AI, producing high-quality and diverse content. However, they inevitably memorize training images or videos, subsequently replicating their concepts, content, or styles…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Wenhao Wang , Yifan Sun , Zongxin Yang , Zhengdong Hu , Zhentao Tan , Yi Yang
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