3D Object Detection in Substation Scene Based on Voxelization.

Aiming at the problem of low detection accuracy caused by insufficient target feature extraction in substation 3D scene, a voxelization-based 3D object detection model AugSecond for substation scene is proposed, which is designed based on the Second network structure. It introduces a triple attention mechanism in the voxel feature encoding stage, which focuses on multi-dimensional attention to enhance the key information of the target and reduce the interference of irrelevant feature information. It designes asymmetric sparse convolutional networks, uses asymmetric convolution to improve convolutional kernel representation capabilities and fuses multi-scale features to enrich target geometry information. Meanwhile, the position regression loss is optimized, and CIoU Loss is used to further consider the geometric correlation between bounding boxes to speed up the network convergence. Experiments on self-built power scene data sets and public data sets show that compared with the benchmark model, AugSecond model significantly improves recognition accuracy and has real-time reasoning speed, which proves the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]