A new annotation-free pipeline converts skin pixels into ITA distributions, measures skin-tone differences with a signed distance, and reweights the loss to reduce the correlation between skin tone and model performance.
Skin deep: Investigating subjectivity in skin tone annotations for computer vision benchmark datasets
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Evaluating Fairness and Mitigating Bias in Machine Learning: A Novel Technique using Tensor Data and Bayesian Regression
A new annotation-free pipeline converts skin pixels into ITA distributions, measures skin-tone differences with a signed distance, and reweights the loss to reduce the correlation between skin tone and model performance.