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Modern diffusion models have set the state-of-the-art in AI image generation. Their success is due, in part, to training on Internet-scale data which often includes copyrighted work. This prompts questions about the extent to which these…

计算机视觉与模式识别 · 计算机科学 2023-07-11 Stephen Casper , Zifan Guo , Shreya Mogulothu , Zachary Marinov , Chinmay Deshpande , Rui-Jie Yew , Zheng Dai , Dylan Hadfield-Menell

The booming use of text-to-image generative models has raised concerns about their high risk of producing copyright-infringing content. While probabilistic copyright protection methods provide a probabilistic guarantee against such…

密码学与安全 · 计算机科学 2024-04-03 Xiang Li , Qianli Shen , Kenji Kawaguchi

Generative art using Diffusion models has achieved remarkable performance in image generation and text-to-image tasks. However, the increasing demand for training data in generative art raises significant concerns about copyright…

机器学习 · 计算机科学 2024-11-07 Zhuan Shi , Yifei Song , Xiaoli Tang , Lingjuan Lyu , Boi Faltings

Visual Generative AI models have demonstrated remarkable capability in generating high-quality images from user inputs like text prompts. However, because these models have billions of parameters, they risk memorizing certain parts of the…

计算机视觉与模式识别 · 计算机科学 2025-12-18 Lena Reissinger , Yuanyuan Li , Anna-Carolina Haensch , Neeraj Sarna

Diffusion-based text-to-image models have shown immense potential for various image-related tasks. However, despite their prominence and popularity, customizing these models using unauthorized data also brings serious privacy and…

计算机视觉与模式识别 · 计算机科学 2024-12-30 Sen Peng , Jijia Yang , Mingyue Wang , Jianfei He , Xiaohua Jia

Diffusion-based image generation models, such as Stable Diffusion or DALL-E 2, are able to learn from given images and generate high-quality samples following the guidance from prompts. For instance, they can be used to create artistic…

计算机视觉与模式识别 · 计算机科学 2023-10-31 Bochuan Cao , Changjiang Li , Ting Wang , Jinyuan Jia , Bo Li , Jinghui Chen

As generative Artificial Intelligence (genAI) technologies proliferate across sectors, they offer significant benefits but also risk exacerbating discrimination. This chapter explores how genAI intersects with non-discrimination laws,…

计算机与社会 · 计算机科学 2025-03-10 Philipp Hacker

Cross-Modal learning tasks have picked up pace in recent times. With plethora of applications in diverse areas, generation of novel content using multiple modalities of data has remained a challenging problem. To address the same, various…

计算机视觉与模式识别 · 计算机科学 2023-07-12 Nikhil Verma

Artists are increasingly concerned about advancements in image generation models that can closely replicate their unique artistic styles. In response, several protection tools against style mimicry have been developed that incorporate small…

密码学与安全 · 计算机科学 2025-02-12 Robert Hönig , Javier Rando , Nicholas Carlini , Florian Tramèr

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…

人工智能 · 计算机科学 2025-08-22 Zhixiang Guo , Siyuan Liang , Aishan Liu , Dacheng Tao

Recently, Diffusion Models (DMs) boost a wave in AI for Art yet raise new copyright concerns, where infringers benefit from using unauthorized paintings to train DMs to generate novel paintings in a similar style. To address these emerging…

计算机视觉与模式识别 · 计算机科学 2023-06-07 Chumeng Liang , Xiaoyu Wu , Yang Hua , Jiaru Zhang , Yiming Xue , Tao Song , Zhengui Xue , Ruhui Ma , Haibing Guan

Stable Diffusion has established itself as a foundation model in generative AI artistic applications, receiving widespread research and application. Some recent fine-tuning methods have made it feasible for individuals to implant…

计算机视觉与模式识别 · 计算机科学 2024-06-25 Zhengyue Zhao , Jinhao Duan , Kaidi Xu , Chenan Wang , Rui Zhang , Zidong Du , Qi Guo , Xing Hu

Diffusion Models (DMs) have shown remarkable capabilities in various image-generation tasks. However, there are growing concerns that DMs could be used to imitate unauthorized creations and thus raise copyright issues. To address this…

计算机视觉与模式识别 · 计算机科学 2024-04-22 Peifei Zhu , Tsubasa Takahashi , Hirokatsu Kataoka

The impressive achievements of generative models in creating high-quality videos have raised concerns about digital integrity and privacy vulnerabilities. Recent works to combat Deepfakes videos have developed detectors that are highly…

计算机视觉与模式识别 · 计算机科学 2024-06-17 Qingyuan Liu , Pengyuan Shi , Yun-Yun Tsai , Chengzhi Mao , Junfeng Yang

There is a growing concern that generative AI models will generate outputs closely resembling the copyrighted materials for which they are trained. This worry has intensified as the quality and complexity of generative models have immensely…

机器学习 · 计算机科学 2024-03-26 Niva Elkin-Koren , Uri Hacohen , Roi Livni , Shay Moran

Generative AI (GenAI) is transforming filmmaking, equipping artists with tools like text-to-image and image-to-video diffusion, neural radiance fields, avatar generation, and 3D synthesis. This paper examines the adoption of these…

Generative AI has unleashed the power of content generation and it has also unwittingly opened the pandora box of realistic deepfake causing a number of social hazards and harm to businesses and personal reputation. The investigation &…

人工智能 · 计算机科学 2026-01-13 Prasanna Kumar

Generative Artificial Intelligence (AI) is a cutting-edge technology capable of producing text, images, and various media content leveraging generative models and user prompts. Between 2022 and 2023, generative AI surged in popularity with…

人工智能 · 计算机科学 2023-10-27 Nouar AlDahoul , Joseph Hong , Matteo Varvello , Yasir Zaki

With the rapid development of generative technology, current generative models can generate high-fidelity digital content and edit it in a controlled manner. However, there is a risk that malicious individuals might misuse these…

计算机视觉与模式识别 · 计算机科学 2025-08-06 Junjie Cao , Kaizhou Li , Xinchun Yu , Hongxiang Li , Xiaoping Zhang

Illegitimate reproduction, distribution and derivation of Deep Neural Network (DNN) models can inflict economic loss, reputation damage and even privacy infringement. Passive DNN intellectual property (IP) protection methods such as…

密码学与安全 · 计算机科学 2025-06-02 Chaohui Xu , Qi Cui , Jinxin Dong , Weiyang He , Chip-Hong Chang