Corpus ID: 160009486

GAPNet: Graph Attention based Point Neural Network for Exploiting Local Feature of Point Cloud

@article{Chen2019GAPNetGA,
  title={GAPNet: Graph Attention based Point Neural Network for Exploiting Local Feature of Point Cloud},
  author={C. Chen and L. Z. Fragonara and A. Tsourdos},
  journal={ArXiv},
  year={2019},
  volume={abs/1905.08705}
}
  • C. Chen, L. Z. Fragonara, A. Tsourdos
  • Published 2019
  • Computer Science
  • ArXiv
  • Exploiting fine-grained semantic features on point cloud is still challenging due to its irregular and sparse structure in a non-Euclidean space. [...] Key Method Firstly, we introduce a GAPLayer to learn attention features for each point by highlighting different attention weights on neighborhood. Secondly, in order to exploit sufficient features, a multi-head mechanism is employed to allow GAPLayer to aggregate different features from independent heads.Expand Abstract
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    References

    SHOWING 1-10 OF 31 REFERENCES
    Mining Point Cloud Local Structures by Kernel Correlation and Graph Pooling
    • 194
    • PDF
    Dynamic Graph CNN for Learning on Point Clouds
    • 974
    • Highly Influential
    • PDF
    PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
    • 2,234
    • PDF
    A Graph-CNN for 3D Point Cloud Classification
    • Yingxue Zhang, M. Rabbat
    • Computer Science, Mathematics
    • 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
    • 2018
    • 42
    • Highly Influential
    • PDF
    PointCNN: Convolution On X-Transformed Points
    • 521
    • PDF
    Graph Attention Networks
    • 2,516
    • PDF
    PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
    • 3,515
    • Highly Influential
    • PDF
    VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
    • Yin Zhou, Oncel Tuzel
    • Computer Science
    • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
    • 2018
    • 886
    • PDF
    Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
    • 2,615
    • Highly Influential
    • PDF
    Dominant Set Clustering and Pooling for Multi-View 3D Object Recognition
    • 91
    • PDF