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Paper Detail

Paper ID3D-2.5
Paper Title LINKED ATTENTION-BASED DYNAMIC GRAPH CONVOLUTION MODULE FOR POINT CLOUD CLASSIFICATION
Authors Xiao-Long Lu, Bao-Di Liu, Wei-Feng Liu, Kai Zhang, China University of Petroleum (East China), China; Ye Li, Qilu University of Technology (Shandong Academy of Sciences), China; Xiaoping Lu, Haier Industrial Intelligence Institute Co., Ltd, China
Session3D-2: Point Cloud Processing 2
LocationArea J
Session Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Time:Wednesday, 22 September, 08:00 - 09:30
Presentation Poster
Topic Three-Dimensional Image and Video Processing: Point cloud processing
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract With the rapid development of 3D technology, point cloud data is becoming more and more popular, which arouses researchers’ interest. But its properties – irregularity and disorder – make it difficult to analyze. In this work, we combine the attention module with the dynamic graph convolutional neural network to pay attention to the target’s critical part. Then, the modules are densely connected to guarantee that each layer is fully utilized. Finally, we carry out experiments on several benchmark datasets to verify the proposed model and achieve state-of-the-art performance.