The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/ad62994b-46b2-43fd-8cf4-83eddb88c494

Strafforello, Ombretta; Kayhan, Osman; van Gemert, Jan (2024): Code underlying the publication: "Humans disagree with the IoU for measuring object detector localization error.". Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/ad62994b-46b2-43fd-8cf4-83eddb88c494.v1

Software

• Artificial Intelligence and Image Processing
• Information and Computing Sciences

Human preference, Intersection over Union (IoU), Object detection

CC0

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by Ombretta Strafforello , Osman Kayhan , Jan van Gemert

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. In this repository, we provide a Jupyter notebook containing the code for our data analysis.

• 2024-05-24 first online, published, posted

4TU.ResearchData

Jupyter Notebook (.ipynb)

Humans Disagree With the IoU for Measuring Object Detector Localization Error

TU Delft, TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Intelligent Systems, Computer Vision Lab
TNO, Netherlands Organisation for Applied Scientific Research, Intelligent Imaging Group