Methods › Computer Vision › Image Model Blocks › CSPResNeXt Block

CSPResNeXt Block

3 papers tagged archive 2025-07-28

Introduced by Chien-Yao Wang et al. in CSPNet: A New Backbone that can Enhance Learning Capability of CNN

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

CSPResNeXt Block is an extended ResNext Block where we partition the feature map of the base layer into two parts and then merge them through a cross-stage hierarchy. The use of a split and merge strategy allows for more gradient flow through the network.

PaperSourceSee Code · Tianxiaomo/pytorch-YOLOv4

Papers archive 2025-07-28

3 shown of 3, 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.

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.

TaskPapers
Object Detection2
Real-Time Object Detection2
Attribute1
BIG-bench Machine Learning1
Computed Tomography (CT)1
Data Augmentation1
Image Classification1
Object1

Usage over time archive 2025-07-28

Papers per year tagged with CSPResNeXt Block: 2019 to 2024, peak 1 1 0 2019: 1 paper 2019 2020: 1 paper 2020 2021: 0 papers 2021 2022: 0 papers 2022 2023: 0 papers 2023 2024: 1 paper 2024
Papers per year the archive tags with this method, by the paper's archive date (3 dated). Bars are counts, not a trend claim.

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

Image Model BlocksSkip Connection Blocks

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