Methods › General › Loss Functions › PIoU Loss
PIoU Loss
Introduced by Zhiming Chen et al. in PIoU Loss: Towards Accurate Oriented Object Detection in Complex Environments
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
PIoU Loss is a loss function for oriented object detection which is formulated to exploit both the angle and IoU for accurate oriented bounding box regression. The PIoU loss is derived from IoU metric with a pixel-wise form.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
-
PIoU Loss: Towards Accurate Oriented Object Detection in Complex Environments 19 Jul 2020 · 1 repository · arXiv:2007.09584Syntology ran 1 of 1 samples · 0 unverified
Tasks archive 2025-07-28
5 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Object Detection | 1 |
| Object Detection In Aerial Images | 1 |
| One-stage Anchor-free Oriented Object Detection | 1 |
| Oriented Object Detection | 1 |
| object-detection | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections