Methods › Computer Vision › Vision Transformers › Twins-PCPVT
Twins-PCPVT
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Twins-PCPVT is a type of vision transformer that combines global attention, specifically the global sub-sampled attention as proposed in Pyramid Vision Transformer, with conditional position encodings (CPE) to replace the absolute position encodings used in PVT.
The position encoding generator (PEG), which generates the CPE, is placed after the first encoder block of each stage. The simplest form of PEG is used, i.e., a 2D depth-wise convolution without batch normalization. For image-level classification, following CPVT, the class token is removed and global average pooling is used at the end of the stage. For other vision tasks, the design of PVT is followed.
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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Twins: Revisiting the Design of Spatial Attention in Vision Transformers 28 Apr 2021 · 9 repositories · arXiv:2104.13840Syntology ran 0 of 2 samples · 2 unverified · 2 pointer-only (licence)
Tasks archive 2025-07-28
2 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 |
|---|---|
| Image Classification | 1 |
| Semantic 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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