Skip to content

Latest commit

 

History

History
33 lines (24 loc) · 2.99 KB

README.md

File metadata and controls

33 lines (24 loc) · 2.99 KB
Raw

Algorithmic Fairness in Natural and GAN Generated Image Detection Systems

Exploring Fairness in Pre-trained Visual Transformer based Natural and GAN Generated Image Detection Systems and Understanding the Impact of Image Compression in Fairness
Manjary P Gangana, Anoop Kb, and Lajish V La
a Department of Computer Science, University of Calicut, India
b School of Psychology, Queen's University Belfast, UK

📝 Paper : http://arxiv.org/abs/2310.12076
🌏 Link: https://dcs.uoc.ac.in/cida/projects/dif/Imageforgeryfairness.html (will be available along with the publication)

Abstract: It is not only sufficient to construct computational models that can accurately classify or detect fake images from real images taken from a camera, but it is also important to ensure whether these computational models are fair enough or produce biased outcomes that can eventually harm certain social groups or cause serious security threats. Exploring fairness in forensic algorithms is an initial step towards correcting these biases. Since visual transformers are recently being widely used in most image classification based tasks due to their capability to produce high accuracies, this study tries to explore bias in the transformer based image forensic algorithms that classify natural and GAN generated images. By procuring a bias evaluation corpora, this study analyzes bias in gender, racial, affective, and intersectional domains using a wide set of individual and pairwise bias evaluation measures. As the generalizability of the algorithms against image compression is an important factor to be considered in forensic tasks, this study also analyzes the role of image compression on model bias. Hence to study the impact of image compression on model bias, a two phase evaluation setting is followed, where a set of experiments is carried out in the uncompressed evaluation setting and the other in the compressed evaluation setting.

For other inquiries, please contact:
Manjary P Gangan 📧 manjaryp_dcs@uoc.ac.in 🌏 website
Anoop K 📧 a.kadan@qub.ac.uk 🌏 website
Lajish V L 📧 lajish@uoc.ac.in 🌏 website

Citation

@article{gangan2023exploring,
      title={Exploring Fairness in Pre-trained Visual Transformer based Natural and GAN Generated Image Detection Systems and Understanding the Impact of Image Compression in Fairness}, 
      author={{Manjary P. Gangan} and {Anoop Kadan} and {Lajish V L}},
      year={2023},
      eprint={2310.12076},
      archivePrefix={arXiv},
      doi={https://doi.org/10.48550/arXiv.2310.12076}
}