# How is Average Recall (AR) calculated for an object detection model?

After looking around the internet (including this paper, I cannot seem to find a satisfactory explanation of the Average Recall (AR) metric. On the COCO website, it describes AR as: "the maximum recall given a fixed number of detections per image, averaged over categories and IoUs".

What does "maximum recall" mean here?

I was wondering if someone could give a reference or a high level overview of the AR calculation algorithm.

Thanks!