Methods › Computer Vision › Object Detection Models › PAFNet
Paddle Anchor Free Network
PAFNet
Introduced by Ying Xin et al. in PAFNet: An Efficient Anchor-Free Object Detector Guidance
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
PAFNet is an anchor-free detector for object detection that removes pre-defined anchors and regresses the locations directly, which can achieve higher efficiency. The overall network is composed of a backbone, an up-sampling module, an AGS module, a localization branch and a regression branch. Specifically, ResNet50-vd is chosen as the backbone for server side, and MobileNetV3 for mobile side. Besides, for mobile side, we replace traditional convolution layers with lite convolution operators.
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.
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PAFNet: An Efficient Anchor-Free Object Detector Guidance 28 Apr 2021 · 1 repository · arXiv:2104.13534
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 |
|---|---|
| CPU | 1 |
| GPU | 1 |
| Object | 1 |
| 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
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