Methods › General › Skip Connection Blocks › Hierarchical-Split Block
Hierarchical-Split Block
Introduced by Pengcheng Yuan et al. in HS-ResNet: Hierarchical-Split Block on Convolutional Neural Network
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Hierarchical-Split Block is a representational block for multi-scale feature representations. It contains many hierarchical split and concatenate connections within one single residual block.
Specifically, ordinary feature maps in deep neural networks are split into s groups, each with w channels. As shown in the Figure, only the first group of filters can be straightly connected to next layer. The second group of feature maps are sent to a convolution of 3 ×3 filters to extract features firstly, then the output feature maps are split into two sub-groups in the channel dimension. One sub-group of feature maps straightly connected to next layer, while the other sub-group is concatenated with the next group of input feature maps in the channel dimension. The concatenated feature maps are operated by a set of 3 ×3 convolutional filters. This process repeats several times until the rest of input feature maps are processed. Finally, features maps from all input groups are concatenated and sent to another layer of 1 ×1 filters to rebuild the features.
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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HS-ResNet: Hierarchical-Split Block on Convolutional Neural Network 15 Oct 2020 · 2 repositories · arXiv:2010.07621
Tasks archive 2025-07-28
8 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 |
| Image Segmentation | 1 |
| Instance Segmentation | 1 |
| Object Detection | 1 |
| Segmentation | 1 |
| Semantic Segmentation | 1 |
| image-classification | 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
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