Methods › Computer Vision › Human Object Interaction Detectors › VSGNet

Visual-Spatial-Graph Network

VSGNet

1 paper tagged archive 2025-07-28

Introduced by Oytun Ulutan et al. in VSGNet: Spatial Attention Network for Detecting Human Object Interactions Using Graph Convolutions

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

Visual-Spatial-Graph Network (VSGNet) is a network for human-object interaction detection. It extracts visual features from the image representing the human-object pair, refines the features with spatial configurations of the pair, and utilizes the structural connections between the pair via graph convolutions.

PaperSource

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.

Tasks archive 2025-07-28

3 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
Human-Object Interaction Detection1
Object1
Spatial Reasoning1

Usage over time archive 2025-07-28

Papers per year tagged with VSGNet: 2020 to 2020, peak 1 1 0 2020: 1 paper 2020
Papers per year the archive tags with this method, by the paper's archive date (1 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

Human Object Interaction Detectors

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