Paper ID | 3D-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 | ||
Session | 3D-2: Point Cloud Processing 2 | ||
Location | Area 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. |