Methods › Computer Vision › Instance Segmentation Models › GCNet

GCNet

11 papers tagged archive 2025-07-28

Introduced by Yue Cao et al. in GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond

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

A Global Context Network, or GCNet, utilises global context blocks to model long-range dependencies in images. It is based on the Non-Local Network, but it modifies the architecture so less computation is required. Global context blocks are applied to multiple layers in a backbone network to construct the GCNet.

PaperSourceSee Code · xvjiarui/GCNet

Papers archive 2025-07-28

11 shown of 11, 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

18 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 Detection3
Decoder2
Instance Segmentation2
Stereo Matching2
Disparity Estimation1
Graph Neural Network1
Management1
Metric Learning1
Multi-Object Tracking1
Object1
Object Recognition1
Object Tracking1
Point Cloud Registration1
Prediction1
Real-Time Semantic Segmentation1
Robot Navigation1
Semantic Segmentation1
object-detection1

Usage over time archive 2025-07-28

Papers per year tagged with GCNet: 2019 to 2025, peak 4 4 0 2019: 1 paper 2019 2020: 2 papers 2020 2021: 2 papers 2021 2022: 4 papers 2022 2023: 1 paper 2023 2024: 0 papers 2024 2025: 1 paper 2025
Papers per year the archive tags with this method, by the paper's archive date (11 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

Instance Segmentation ModelsObject Detection Models

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