Methods › Computer Vision › Convolutions › DAU-ConvNet
Displaced Aggregation Units
DAU-ConvNet
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Displaced Aggregation Unit replaces classic convolution layer in ConvNets with learnable positions of units. This introduces explicit structure of hierarchical compositions and results in several benefits:
- fully adjustable and learnable receptive fields through spatially-adjustable filter units
- reduced parameters for spatial coverage efficient inference
- decupling of the parameters from the receptive field sizes
More information can be found here.
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.
-
Spatially-Adaptive Filter Units for Compact and Efficient Deep Neural Networks 20 Feb 2019 · 3 repositories · arXiv:1902.07474
-
Spatially-Adaptive Filter Units for Deep Neural Networks 30 Nov 2017 · 2 repositories · arXiv:1711.11473
Tasks archive 2025-07-28
4 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 | 2 |
| Semantic Segmentation | 2 |
| Blind Image Deblurring | 1 |
| image-classification | 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