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Related papers: We are not able to identify AI-generated images

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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

The high level of photorealism in state-of-the-art diffusion models like Midjourney, Stable Diffusion, and Firefly makes it difficult for untrained humans to distinguish between real photographs and AI-generated images. To address this…

Human-Computer Interaction · Computer Science 2024-06-14 Negar Kamali , Karyn Nakamura , Angelos Chatzimparmpas , Jessica Hullman , Matthew Groh

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

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

Generative AI now produces photorealistic portraits that circulate widely in social and newslike contexts. Human ability to distinguish real from synthetic faces is time-sensitive because image generators continue to improve while public…

Human-Computer Interaction · Computer Science 2026-03-26 Sunwhi Kim , Sunyul Kim

Recent advancements in Artificial Intelligence have led to remarkable improvements in generating realistic human faces. While these advancements demonstrate significant progress in generative models, they also raise concerns about the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-25 Jin Huang , Subhadra Gopalakrishnan , Trisha Mittal , Jake Zuena , Jaclyn Pytlarz

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

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

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

In recent years, deep learning methods have become increasingly capable of generating near photorealistic pictures and humanlike text up to the point that humans can no longer recognize what is real and what is AI-generated. Concerningly,…

Social and Information Networks · Computer Science 2022-09-16 Sippo Rossi , Youngjin Kwon , Odd Harald Auglend , Raghava Rao Mukkamala , Matti Rossi , Jason Thatcher

Deep fakes became extremely popular in the last years, also thanks to their increasing realism. Therefore, there is the need to measures human's ability to distinguish between real and synthetic face images when confronted with cutting-edge…

Computer Vision and Pattern Recognition · Computer Science 2022-01-12 Federica Lago , Cecilia Pasquini , Rainer Böhme , Hélène Dumont , Valérie Goffaux , Giulia Boato

Digital images are ubiquitous in our modern lives, with uses ranging from social media to news, and even scientific papers. For this reason, it is crucial evaluate how accurate people are when performing the task of identify doctored…

Graphics · Computer Science 2016-01-14 Victor Schetinger , Manuel M. Oliveira , Roberto da Silva , Tiago J. Carvalho

In the realm of digital media, the advent of AI-generated synthetic images has introduced significant challenges in distinguishing between real and fabricated visual content. These images, often indistinguishable from authentic ones, pose a…

Computer Vision and Pattern Recognition · Computer Science 2024-05-27 Yuyang Wang , Yizhi Hao , Amando Xu Cong

AI-based image generation has continued to rapidly improve, producing increasingly more realistic images with fewer obvious visual flaws. AI-generated images are being used to create fake online profiles which in turn are being used for…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Gonzalo J. Aniano Porcile , Jack Gindi , Shivansh Mundra , James R. Verbus , Hany Farid

AI-generated media has become a threat to our digital society as we know it. These forgeries can be created automatically and on a large scale based on publicly available technology. Recognizing this challenge, academics and practitioners…

Cryptography and Security · Computer Science 2023-12-12 Joel Frank , Franziska Herbert , Jonas Ricker , Lea Schönherr , Thorsten Eisenhofer , Asja Fischer , Markus Dürmuth , Thorsten Holz

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

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,…

Recent advances in the field of generative artificial intelligence (AI) have blurred the lines between authentic and machine-generated content, making it almost impossible for humans to distinguish between such media. One notable…

Cryptography and Security · Computer Science 2024-10-04 Jonas Ricker , Dennis Assenmacher , Thorsten Holz , Asja Fischer , Erwin Quiring

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

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
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