When a global electronics maker came to DefinedCrowd with the goal of building more inclusive facial-recognition technology, the objective seemed simple: If given just one portrait containing a family of East-Asian descent, the model needed to be able to identify each individual person while also understanding that individual’s place within the family context. I.e. recognizing a little girl’s face as a little girl’s face as well as correctly identifying her as a “daughter.”
Training such a model was no easy task, and required accurately annotated images that adhered to highly specific criteria: Each portrait needed to contain children, have a minimum resolution of 640×640 pixels, and represent a wide variety of indoor lighting conditions.
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