Humans disagree with the IoU for measuring object detector localization error

Abstract

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

Publication
Proceedings of the 29th IEEE International Conference on Image Processing (ICIP 2022)
Osman Semih Kayhan
Osman Semih Kayhan
PhD Candidate

Interests include equivariant CNNs and context in object detection.

Jan van Gemert
Jan van Gemert
Associate Professor

Head of the CV Lab.