Characterizing Photorealism and Artifacts in Diffusion Model-Generated Images
Journal:
arXiv
Published Date:
Feb 17, 2025
Abstract
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 posed by photorealistic AI-generated images, we conducted a large-scale
experiment measuring human detection accuracy on 450 diffusion-model generated
images and 149 real images. Based on collecting 749,828 observations and 34,675
comments from 50,444 participants, we find that scene complexity of an image,
artifact types within an image, display time of an image, and human curation of
AI-generated images all play significant roles in how accurately people
distinguish real from AI-generated images. Additionally, we propose a taxonomy
characterizing artifacts often appearing in images generated by diffusion
models. Our empirical observations and taxonomy offer nuanced insights into the
capabilities and limitations of diffusion models to generate photorealistic
images in 2024.
