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The localization quality of automatic object detectors is typically evaluatedby the Intersection over Union (IoU) score. In this work, we show that humanshave a different view on localization quality. To evaluate this, we conduct asurvey with more than 70 participants. Results show that for localizationerrors with the exact same IoU score, humans might not consider that theseerrors are equal, and express a preference. Our work is the first to evaluateIoU with humans and makes it clear that relying on IoU scores alone to evaluatelocalization errors might not be sufficient.

Humans disagree with the IoU for measuring object detector localization error