Methods › Computer Vision › Feature Pyramid Blocks › MLFPN
MLFPN
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.
Multi-Level Feature Pyramid Network, or MLFPN, is a feature pyramid block used in object detection models, notably M2Det. We first fuse multi-level features (i.e. multiple layers) extracted by a backbone as a base feature, and then feed it into a block of alternating joint Thinned U-shape Modules (TUM) and Feature Fusion Modules (FFM) to extract more representative, multi-level multi-scale features. Finally, we gather up the feature maps with equivalent scales to construct the final feature pyramid for object detection. Decoder layers that form the final feature pyramid are much deeper than the layers in the backbone, namely, they are more representative. Moreover, each feature map in the final feature pyramid consists of the decoder layers from multiple levels. Hence, the feature pyramid block is called Multi-Level Feature Pyramid Network (MLFPN).
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
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