A study of Biases in Common Face Recognition Datasets

12/08/2021

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by   Kanishk Rath, et al.

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The performance of commonly used facial recognition datasets have been studied when applied on a racially diverse population. A need for racial diversity in the training data set has been observed to improve the outputs of the models. Further, impact of Covid-19 pandemic on facial recognition technologies in terms of Mask detection models and corresponding datasets have been studied. Finally, a GAN based tool has been used for modifying image using sentences to obtain racial or gender diverse outcome. Potential implications of GAN based tools for such image manipulation, with potential solution to avoid misuse of such software have been discussed.