3D Object Detection Based on Graph Network and Voxel
HUANG Wei
JIN Zhong
Abstract：The voxel-based 3D object detection model outperforms the graph-based model in terms of speed and detection ac-curacy,but the use of average pooling operation during voxelization leads to loss of detail information,which degrades the perfor-mance of the model to some extent.The proposed method uses a graph network to explicitly construct the topology to capture local point cloud detail information during voxelization to solve the information loss in voxelization,and achieves a balance of speed and detection accuracy by cropping the voxel backbone network.The proposed method is experimented on the KITTI,a publicly avail-able 3D object detection database,for the detection of car class objects,and achieves 84.85%average precision(AP)detection re-sults,which exceedes some advanced 3D object detection models.
Keywords：3D object detectiongraph networkvoxelizationfeature processing
Publication Date：2025-04-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 980-983 )