Papers › BandRe: Rethinking Band-Pass Filters for Scale-Wise Object Detection Evaluation
BandRe: Rethinking Band-Pass Filters for Scale-Wise Object Detection Evaluation
Yosuke Shinya
Scale-wise evaluation of object detectors is important for real-world applications. However, existing metrics are either coarse or not sufficiently reliable. In this paper, we propose novel scale-wise metrics that strike a balance between fineness and reliability, using a filter bank consisting of triangular and trapezoidal band-pass filters. We conduct experiments with two methods on two datasets and show that the proposed metrics can highlight the differences between the methods and between the datasets. Code is available at https://github.com/shinya7y/UniverseNet .
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Small Object Detection | SOD4SB Private Test | GFL + Test Time Augmentation | AP50 | 23.7 | #2 of 5 | Archive leaderboard | report |
| Small Object Detection | SOD4SB Public Test | GFL + Test Time Augmentation | AP50 | 73.1 | #2 of 5 | Archive leaderboard | report |
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