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Diffusion model-generated images can appear indistinguishable from authentic photographs, but these images often contain artifacts and implausibilities that reveal their AI-generated provenance. Given the challenge to public trust in media…

Human-Computer Interaction · Computer Science 2025-02-18 Negar Kamali , Karyn Nakamura , Aakriti Kumar , Angelos Chatzimparmpas , Jessica Hullman , Matthew Groh

AI-generated images are now pervasive online, yet many people believe they can easily tell them apart from real photographs. We test this assumption through an interactive web experiment where participants classify 20 images as real or…

Artificial Intelligence · Computer Science 2025-12-30 Adrien Pavão

Artificial Intelligence (AI) tools have become incredibly powerful in generating synthetic images. Of particular concern are generated images that resemble photographs as they aspire to represent real world events. Synthetic photographs may…

Computers and Society · Computer Science 2024-08-14 Melanie Mathys , Marco Willi , Raphael Meier

The advent of generative AI images has completely disrupted the art world. Distinguishing AI generated images from human art is a challenging problem whose impact is growing over time. A failure to address this problem allows bad actors to…

Computer Vision and Pattern Recognition · Computer Science 2024-07-04 Anna Yoo Jeong Ha , Josephine Passananti , Ronik Bhaskar , Shawn Shan , Reid Southen , Haitao Zheng , Ben Y. Zhao

Diffusion models are able to produce AI-generated images that are almost indistinguishable from real ones. This raises concerns about their potential misuse and poses substantial challenges for detecting them. Many existing detectors rely…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Xinyi Qi , Kai Ye , Chengchun Shi , Ying Yang , Hongyi Zhou , Jin Zhu

As AI-powered image generation improves, a key question is how well human beings can differentiate between "real" and AI-generated or modified images. Using data collected from the online game "Real or Not Quiz.", this study investigates…

Human-Computer Interaction · Computer Science 2025-07-28 Thomas Roca , Anthony Cintron Roman , Jehú Torres Vega , Marcelo Duarte , Pengce Wang , Kevin White , Amit Misra , Juan Lavista Ferres

Generative AI models can produce high-quality images based on text prompts. The generated images often appear indistinguishable from images generated by conventional optical photography devices or created by human artists (i.e., real…

Computer Vision and Pattern Recognition · Computer Science 2024-04-24 Yuying Li , Zeyan Liu , Junyi Zhao , Liangqin Ren , Fengjun Li , Jiebo Luo , Bo Luo

Multimodal generative AI systems like Stable Diffusion, DALL-E, and MidJourney have fundamentally changed how synthetic images are created. These tools drive innovation but also enable the spread of misleading content, false information,…

Photos serve as a way for humans to record what they experience in their daily lives, and they are often regarded as trustworthy sources of information. However, there is a growing concern that the advancement of artificial intelligence…

Artificial Intelligence · Computer Science 2023-09-26 Zeyu Lu , Di Huang , Lei Bai , Jingjing Qu , Chengyue Wu , Xihui Liu , Wanli Ouyang

Recent technological advances in synthetic data have enabled the generation of images with such high quality that human beings cannot tell the difference between real-life photographs and Artificial Intelligence (AI) generated images. Given…

Computer Vision and Pattern Recognition · Computer Science 2023-03-27 Jordan J. Bird , Ahmad Lotfi

In the rapidly evolving field of Artificial Intelligence Generated Content (AIGC), a central challenge is distinguishing AI-synthesized images from natural ones. Despite the impressive capabilities of advanced generative models in producing…

Artificial Intelligence · Computer Science 2025-08-12 Renyang Liu , Ziyu Lyu , Wei Zhou , See-Kiong Ng

Advances in generative models have created Artificial Intelligence-Generated Images (AIGIs) nearly indistinguishable from real photographs. Leveraging a large corpus of 30,824 AIGIs collected from Instagram and Twitter, and combining…

Computers and Society · Computer Science 2025-03-19 Qiyao Peng , Yingdan Lu , Yilang Peng , Sijia Qian , Xinyi Liu , Cuihua Shen

The misuse of generative AI in online disinformation campaigns highlights the urgent need for transparent and explainable detection systems. In this work, we investigate how detectors for AI-generated images can be more effective in…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Silvia Poletti , Justin Ilyes , Marcel Hasenbalg , David Fischinger , Martin Boyer

The extraordinary ability of generative models enabled the generation of images with such high quality that human beings cannot distinguish Artificial Intelligence (AI) generated images from real-life photographs. The development of…

Computer Vision and Pattern Recognition · Computer Science 2024-02-20 Yan Hong , Jianfu Zhang

The widespread and rapid adoption of AI-generated content, created by models such as Generative Adversarial Networks (GANs) and Diffusion Models, has revolutionized the digital media landscape by allowing efficient and creative content…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Aadi Srivastava , Vignesh Natarajkumar , Utkarsh Bheemanaboyna , Devisree Akashapu , Nagraj Gaonkar , Archit Joshi

We fine-tuned a foundational stable diffusion model using X-ray scattering images and their corresponding descriptions to generate new scientific images from given prompts. However, some of the generated images exhibit significant…

Image and Video Processing · Electrical Eng. & Systems 2024-08-26 Zhuowen Zhao , Xiaoya Chong , Tanny Chavez , Alexander Hexemer

The image deepfake detection task has been greatly addressed by the scientific community to discriminate real images from those generated by Artificial Intelligence (AI) models: a binary classification task. In this work, the deepfake…

Computer Vision and Pattern Recognition · Computer Science 2023-03-02 Luca Guarnera , Oliver Giudice , Sebastiano Battiato

Recent advances in visual generative models have enabled the creation of highly realistic, fully AI-generated images without relying on real source content. While beneficial for many applications, these models also pose significant societal…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Qijie Xu , Can Wang , Jiawei Chen , Siwei Lyu , Defang Chen

AI-based text-to-image generation has undergone a significant leap in the production of visually comprehensive and aesthetic imagery over the past year, to the point where differentiating between a man-made piece of art and an AI-generated…

Computers and Society · Computer Science 2023-06-06 Sarah K. Amer

The latest developments in Artificial Intelligence include diffusion generative models, quite popular tools which can produce original images both unconditionally and, in some cases, conditioned by some inputs provided by the user. Apart…

Computer Vision and Pattern Recognition · Computer Science 2023-02-13 Stefano Scotta , Alberto Messina
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