mlsanityData to 7 Oct 2026

GTNet:Guided Transformer Network for Detecting Human-Object Interactions

arXiv 2108.00596 ↗First posted 2 Aug 2021cs.CVcited by 8

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Abstract (arXiv)

The human-object interaction (HOI) detection task refers to localizing humans, localizing objects, and predicting the interactions between each human-object pair. HOI is considered one of the fundamental steps in truly understanding complex visual scenes. For detecting HOI, it is important to utilize relative spatial configurations and object semantics to find salient spatial regions of images that highlight the interactions between human object pairs. This issue is addressed by the novel self-attention based guided transformer network, GTNet. GTNet encodes this spatial contextual information in human and object visual features via self-attention while achieving state of the art results on both the V-COCO and HICO-DET datasets. Code will be made available online.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 54 of its 67 references that are in the map. First posted on arXiv 2 Aug 2021.

Builds on

54 of 67 references.

References · 54

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38 more
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50 most cited of 54 All 54 (JSON)

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Cited by year

Citing papers per year: 2022: 2; 2023: 3; 2024: 2; 2025: 1.

8 papers.

  1. 2022What to look at and where: Semantic and Spatial Refined Transformer for detecting human-object interactionscited by 35
  2. 2023Vision Relation Transformer for Unbiased Scene Graph Generationcited by 18
  3. 2023MethaneMapper: Spectral Absorption aware Hyperspectral Transformer for Methane Detectioncited by 12
  4. 2024A Review of Human-Object Interaction Detectioncited by 5
  5. 2022LOCL: Learning Object-Attribute Composition using Localizationcited by 3
  6. 2023DDS: Decoupled Dynamic Scene-Graph Generation Networkcited by 3
  7. 2024FreeA: Human-object Interaction Detection using Free Annotation Labelscited by 0
  8. 2025ART: Adaptive Relation Tuning for Generalized Relation Predictioncited by 0