mlsanityData to 7 Oct 2026

A Skeleton-aware Graph Convolutional Network for Human-Object Interaction Detection

arXiv 2207.05733 ↗First posted 11 Jul 2022cs.CV cs.AIcited by 3

Not on the map. Why?

Abstract (arXiv)

Detecting human-object interactions is essential for comprehensive understanding of visual scenes. In particular, spatial connections between humans and objects are important cues for reasoning interactions. To this end, we propose a skeleton-aware graph convolutional network for human-object interaction detection, named SGCN4HOI. Our network exploits the spatial connections between human keypoints and object keypoints to capture their fine-grained structural interactions via graph convolutions. It fuses such geometric features with visual features and spatial configuration features obtained from human-object pairs. Furthermore, to better preserve the object structural information and facilitate human-object interaction detection, we propose a novel skeleton-based object keypoints representation. The performance of SGCN4HOI is evaluated in the public benchmark V-COCO dataset. Experimental results show that the proposed approach outperforms the state-of-the-art pose-based models and achieves competitive performance against other models.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 22 of its 37 references that are in the map. First posted on arXiv 11 Jul 2022.

Builds on

22 of 37 references.

References · 22

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  3. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  4. 2020End-to-End Object Detection with Transformerscited by 7,384
  5. 2016Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answeringcited by 2,498
  6. 2018Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognitioncited by 1,199
  7. 2019RepPoints: Point Set Representation for Object Detectioncited by 264
  8. 2021ReDet: A Rotation-equivariant Detector for Aerial Object Detectioncited by 202
  9. 2017Detecting and Recognizing Human-Object Interactionscited by 199
  10. 2015Visual Semantic Role Labelingcited by 188
  11. 2021HOTR: End-to-End Human-Object Interaction Detection with Transformerscited by 183
  12. 2021QPIC: Query-Based Pairwise Human-Object Interaction Detection with Image-Wide Contextual Informationcited by 147
10 more
  1. 2021End-to-End Human Object Interaction Detection with HOI Transformercited by 134
  2. 2020Visual Compositional Learning for Human-Object Interaction Detectioncited by 129
  3. 2018iCAN: Instance-Centric Attention Network for Human-Object Interaction Detectioncited by 126
  4. 2020DRG: Dual Relation Graph for Human-Object Interaction Detectioncited by 117
  5. 2020VSGNet: Spatial Attention Network for Detecting Human Object Interactions Using Graph Convolutionscited by 115
  6. 2020Learning Human-Object Interaction Detection using Interaction Pointscited by 108
  7. 2019Pose-aware Multi-level Feature Network for Human Object Interaction Detectioncited by 88
  8. 2020PaStaNet: Toward Human Activity Knowledge Enginecited by 79
  9. 2020Detecting Human-Object Interactions with Action Co-occurrence Priorscited by 72
  10. 2021Exploiting Scene Graphs for Human-Object Interaction Detectioncited by 22

Built on by

Cited by year

Citing papers per year: 2022: 1; 2023: 1; 2024: 1.

3 papers.