Towards Fairness under Label Bias in Image Segmentation: Impact, Measurement and Mitigation
A Confident Learning framework adapted to segmentation for auditing label bias directly in the training data without a clean, unbiased ground truth is presented, and it is shown that label bias influences subgroup separability in the encoder's feature space, an artifact the authors leverage for bias mitigation rather t...