Face Detection with Bayesian Decision Theory

This project reproduces and extends the Bayes error estimation framework proposed by Ishida et al. (ICLR 2023). Our work focuses on examining how violations of the soft-label assumptions, specifically annotation bias and model miscalibration impact the consistency and reliability of Bayes error estimators.