Methods › Computer Vision › Convolutional Neural Networks › CornerNet-Squeeze Hourglass
CornerNet-Squeeze Hourglass
Introduced by Hei Law et al. in CornerNet-Lite: Efficient Keypoint Based Object Detection
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
CornerNet-Squeeze Hourglass is a convolutional neural network and object detection backbone used in the CornerNet-Squeeze object detector. It uses a modified hourglass module that makes use of a fire module: containing 1x1 convolutions and depthwise convolutions.
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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CornerNet-Lite: Efficient Keypoint Based Object Detection 18 Apr 2019 · 6 repositories · arXiv:1904.08900Syntology ran 1 of 27 samples · 26 unverified
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 | 1 |
| Object Detection | 1 |
| Real-Time 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