111

A Comprehensive Dataset for Human vs. AI Generated Image Detection

Rajarshi Roy
Nasrin Imanpour
Ashhar Aziz
Shashwat Bajpai
Gurpreet Singh
Shwetangshu Biswas
Kapil Wanaskar
Parth Patwa
Subhankar Ghosh
Shreyas Dixit
Nilesh Ranjan Pal
Vipula Rawte
Ritvik Garimella
Gaytri Jena
Vasu Sharma
Vinija Jain
Aman Chadha
Aishwarya Naresh Reganti
Amitava Das
Main:6 Pages
4 Figures
Bibliography:2 Pages
Abstract

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, and manipulated media. As generated images become harder to distinguish from photographs, detecting them has become an urgent priority. To combat this challenge, We release MS COCOAI, a novel dataset for AI generated image detection consisting of 96000 real and synthetic datapoints, built using the MS COCO dataset. To generate synthetic images, we use five generators: Stable Diffusion 3, Stable Diffusion 2.1, SDXL, DALL-E 3, and MidJourney v6. Based on the dataset, we propose two tasks: (1) classifying images as real or generated, and (2) identifying which model produced a given synthetic image. The dataset is available atthis https URL.

View on arXiv
Comments on this paper