Methods › Computer Vision › RoI Feature Extractors › Deformable Position-Sensitive RoI Pooling
Deformable Position-Sensitive RoI Pooling
Introduced by Jifeng Dai et al. in Deformable Convolutional Networks
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Deformable Position-Sensitive RoI Pooling is similar to PS RoI Pooling but it adds an offset to each bin position in the regular bin partition. Offset learning follows the “fully convolutional” spirit. In the top branch, a convolutional layer generates the full spatial resolution offset fields. For each RoI (also for each class), PS RoI pooling is applied on such fields to obtain normalized offsets, which are then transformed to the real offsets, in the same way as in deformable RoI pooling.
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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Deformable Convolutional Networks 17 Mar 2017 · 38 repositories · arXiv:1703.06211Syntology ran 3 of 9 samples · 6 unverified · 3 pointer-only (licence)
Tasks archive 2025-07-28
3 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 | 1 |
| Semantic Segmentation | 1 |
| Vessel 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