FACET: Benchmarking fairness of vision models

Datarows: 31,702 data rows
Image classification
Object detection

FACET is a comprehensive benchmark dataset from Meta AI for evaluating the fairness of vision models across classification, detection, instance segmentation, and visual grounding tasks involving people. FACET helps to measure performance gaps for common use-cases of computer vision models and to answer questions such as:

  • Are models better at classifying people as skateboarders when their perceived gender presentation has more stereotypically male attributes?

  • Are open-vocabulary detection models better at detecting backpackers who are perceived to be younger?

Does not contain segmentation mask and skin tone.