mlsanityData to 7 Oct 2026

Survey of Image Based Graph Neural Networks

arXiv 2106.06307 ↗First posted 11 Jun 2021cs.LG cs.AI cs.CVcited by 7

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Abstract (arXiv)

In this survey paper, we analyze image based graph neural networks and propose a three-step classification approach. We first convert the image into superpixels using the Quickshift algorithm so as to reduce 30% of the input data. The superpixels are subsequently used to generate a region adjacency graph. Finally, the graph is passed through a state-of-art graph convolutional neural network to get classification scores. We also analyze the spatial and spectral convolution filtering techniques in graph neural networks. Spectral-based models perform better than spatial-based models and classical CNN with lesser compute cost.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 30 of its 41 references that are in the map. First posted on arXiv 11 Jun 2021.

Builds on

30 of 41 references.

References · 30

  1. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  2. 2019A Comprehensive Survey on Graph Neural Networkscited by 2,906
  3. 2019Fast Graph Representation Learning with PyTorch Geometriccited by 2,414
  4. 2016Convolutional Neural Networks on Graphs with Fast Localized Spectral Filteringcited by 2,085
  5. 2018Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognitioncited by 1,199
  6. 2016Geometric deep learning on graphs and manifolds using mixture model CNNscited by 468
  7. 2018Neural Relational Inference for Interacting Systemscited by 339
  8. 2017Few-Shot Learning with Graph Neural Networkscited by 324
  9. 2017Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphscited by 307
  10. 2017Relation Networks for Object Detectioncited by 305
  11. 2015Deep Convolutional Networks on Graph-Structured Datacited by 246
  12. 2015Structural-RNN: Deep Learning on Spatio-Temporal Graphscited by 234
18 more
  1. 2017Learning to Represent Programs with Graphscited by 219
  2. 2018Learning Human-Object Interactions by Graph Parsing Neural Networkscited by 176
  3. 2017SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernelscited by 160
  4. 2018Zero-shot Recognition via Semantic Embeddings and Knowledge Graphscited by 155
  5. 2014Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimationcited by 129
  6. 2018Rethinking Knowledge Graph Propagation for Zero-Shot Learningcited by 87
  7. 2018Superpixel Sampling Networkscited by 79
  8. 2017Multi-Label Zero-Shot Learning with Structured Knowledge Graphscited by 72
  9. 2020Superpixel Segmentation with Fully Convolutional Networkscited by 72
  10. 2016The More You Know: Using Knowledge Graphs for Image Classificationcited by 63
  11. 2019Structured agents for physical constructioncited by 50
  12. 2016Semantic Object Parsing with Graph LSTMcited by 44
  13. 2018Deep Reasoning with Knowledge Graph for Social Relationship Understandingcited by 44
  14. 2019Multi-scale Dynamic Graph Convolutional Network for Hyperspectral Image Classificationcited by 31
  15. 2018Learning Region Features for Object Detectioncited by 15
  16. 2018Spectral Multigraph Networks for Discovering and Fusing Relationships in Moleculescited by 9
  17. 2019Image Classification with Hierarchical Multigraph Networkscited by 7
  18. 2016Graph Based Convolutional Neural Networkcited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 1; 2024: 1; 2025: 1; 2026: 2.

7 papers.

  1. 2022Graph Condensation via Receptive Field Distribution Matchingcited by 60
  2. 2022Graph Neural Networks in IoT: A Surveycited by 27
  3. 2024Graph Data Condensation via Self-expressive Graph Structure Reconstructioncited by 18
  4. 2023Graph-based Knowledge Distillation: A survey and experimental evaluationcited by 6
  5. 2025GraphEnet: Event-driven Human Pose Estimation with a Graph Neural Networkcited by 1
  6. 2026Visual graphs for image classification: does the structure affect performance?cited by 0
  7. 2026Low resource cross-modal alignment using HGNN to enhance speech representationcited by 0