Methods › Computer Vision › One-Stage Object Detection Models › M2Det
M2Det
Introduced by Qijie Zhao et al. in M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
M2Det is a one-stage object detection model that utilises a Multi-Level Feature Pyramid Network (MLFPN) to extract features from the input image, and then similar to SSD, produces dense bounding boxes and category scores based on the learned features, followed by the non-maximum suppression (NMS) operation to produce the final results.
Papers archive 2025-07-28
2 shown of 2, 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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Towards Robust Visual Information Extraction in Real World: New Dataset and Novel Solution 24 Jan 2021 · 1 repository · arXiv:2102.06732
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M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid Network 12 Nov 2018 · 11 repositories · arXiv:1811.04533Syntology ran 1 of 1 samples · 0 unverified
Tasks archive 2025-07-28
8 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 |
|---|---|
| 3D Feature Matching | 1 |
| Decoder | 1 |
| Object | 1 |
| Object Detection | 1 |
| Text Detection | 1 |
| Text Spotting | 1 |
| document understanding | 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