FACET, a benchmark dataset designed to aid researchers in testing computer vision models for bias, was released by Meta Platforms Inc. earlier this week.
FACET is being launched alongside an update to the open-source DINOv2 toolbox. DINOv2, which was first released in April, is a set of artificial intelligence models aimed to help with computer vision projects. DINOv2 is now accessible under a commercial licence, thanks to recent upgrades.
Meta’s new FACET dataset is intended to aid researchers in determining whether a computer vision model is producing biased results. The company explained in a blog post that measuring AI fairness is difficult using current benchmarking methodologies. FACET, according to Meta, will make the work easier by providing a big evaluation dataset that researchers may use to audit various types of computer vision models.
“The dataset is made up of 32,000 images containing 50,000 people, labelled by expert human annotators for demographic attributes (e.g., perceived gender presentation, perceive
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