Methods › Computer Vision › Convolutional Neural Networks › ConvMLP
ConvMLP
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
ConvMLP is a hierarchical convolutional MLP for visual recognition, which consists of a stage-wise, co-design of convolution layers, and MLPs. The Conv Stage consists of C convolutional blocks with 1×1 and 3×3 kernel sizes. It is repeated M times before a down convolution is utilized to express a level L. The MLP-Conv Stage consists of Channelwise MLPs, with skip layers, and a depthwise convolution. This is repeated M times before a down convolution is utilized to express a level ℒ.
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.
-
ConvMLP: Hierarchical Convolutional MLPs for Vision 9 Sep 2021 · 4 repositories · arXiv:2109.04454Syntology ran 0 of 3 samples · 3 unverified
Tasks archive 2025-07-28
5 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 |
| Instance Segmentation | 1 |
| Object Detection | 1 |
| Semantic Segmentation | 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
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