Methods › Computer Vision › Instance Segmentation Models › BlendMask
BlendMask
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
BlendMask is an instance segmentation framework built on top of the FCOS object detector. The bottom module uses either backbone or FPN features to predict a set of bases. A single convolution layer is added on top of the detection towers to produce attention masks along with each bounding box prediction. For each predicted instance, the blender crops the bases with its bounding box and linearly combine them according the learned attention maps. Note that the Bottom Module can take features either from ‘C’, or ‘P’ as the input.
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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Unifying Instance and Panoptic Segmentation with Dynamic Rank-1 Convolutions 19 Nov 2020 · 0 repositories · arXiv:2011.09796
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BlendMask: Top-Down Meets Bottom-Up for Instance Segmentation 2 Jan 2020 · 9 repositories · arXiv:2001.00309
Tasks archive 2025-07-28
7 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 |
|---|---|
| Instance Segmentation | 2 |
| Segmentation | 2 |
| Semantic Segmentation | 2 |
| GPU | 1 |
| Multi-Task Learning | 1 |
| Panoptic Segmentation | 1 |
| Real-time Instance Segmentation | 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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