2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper ID3D-1.7
Paper Title POINTVIEW-GCN: 3D SHAPE CLASSIFICATION WITH MULTI-VIEW POINT CLOUDS
Authors Seyed Saber Mohammadi, Universita degli Studi di Genova, Istituto Italino di Tecnologia, Italy; Yiming Wang, Istituto Italino di Tecnologia, Deep Visual Learning (DVL), Italy; Alessio Del Bue, Istituto Italino di Tecnologia, Italy
Session3D-1: Point Cloud Processing 1
LocationArea J
Session Time:Tuesday, 21 September, 15:30 - 17:00
Presentation Time:Tuesday, 21 September, 15:30 - 17:00
Presentation Poster
Topic Three-Dimensional Image and Video Processing: Point cloud processing
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract We address 3D shape classification with partial point cloud inputs captured from multiple viewpoints around the object. Different from existing methods that perform classification on the complete point cloud by first registering multi-view capturing, we propose PointView-GCN with multi-level GraphConvolutional Networks (GCNs) to hierarchically aggregate the shape features of single-view point clouds, in order to encode both the geometrical cues of an object and their multi-view relations. With experiments on our novel single-view datasets, we prove that PointView-GCN produces a more descriptive global shape feature which stably improves the classification accuracy by about 5 percents compared to the classifiers with single-view point clouds, and outperforms the state-of-the-art methods with the complete point clouds on ModelNet40.