Methods › Computer Vision › Object Detection Models › TridentNet
TridentNet
Introduced by Yanghao Li et al. in Scale-Aware Trident Networks for Object Detection
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
TridentNet is an object detection architecture that aims to generate scale-specific feature maps with a uniform representational power. A parallel multi-branch architecture is constructed in which each branch shares the same transformation parameters but with different receptive fields. A scale-aware training scheme is used to specialize each branch by sampling object instances of proper scales for training.
Papers archive 2025-07-28
3 shown of 3, 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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Deep learning approaches to building rooftop thermal bridge detection from aerial images 12 Dec 2022 · 1 repository
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DRPN: Making CNN Dynamically Handle Scale Variation 21 Dec 2021 · 0 repositories · arXiv:2112.10963
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Scale-Aware Trident Networks for Object Detection 7 Jan 2019 · 4 repositories · arXiv:1901.01892
Tasks archive 2025-07-28
4 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 | 2 |
| Instance Segmentation | 1 |
| Object | 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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