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Generalized Intersection over Union: A Metric and A Loss ...

Generalized Intersection over Union: A Metric and A loss for Bounding BoxRegressionHamid Rezatofighi1,2 Nathan Tsoi1 JunYoung Gwak1 Amir Sadeghian1,3 Ian Reid2 Silvio Savarese11 Computer Science Department, Stanford University, United states2 School of Computer Science, The University of Adelaide, Australia3 Aibee Inc, over Union (IoU) is the most popular evalu-ation Metric used in the object detection benchmarks. How-ever, there is a gap between optimizing the commonly useddistance losses for regressing the parameters of a boundingbox and maximizing this Metric value. The optimal objec-tive for a Metric is the Metric itself. In the case of axis-aligned 2D bounding boxes, it can be shown thatIoUcanbe directly used as a regression loss .

lem, the authors later introduce focal loss [13], which is orthogonal to the main focus of our paper. Most popular object detectors [20, 21, 3, 12, 13, 16] uti-lize some combination of the bounding box representations and losses mentioned above. These considerable efforts have yielded significant improvement in object detection.

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