TY - GEN
T1 - An Enhanced SqueezeNet Based Network for Real-Time Road-Object Segmentation
AU - Li, Chao
AU - Wei, Xian
AU - Yu, Hui
AU - Guo, Jielong
AU - Tang, Xuan
AU - Zhang, Yuxuan
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - Point cloud image segmentation plays an important role in self-driving. SqueezeSeg network has good performance in terms of accuracy and calculation speed on point cloud segmentation. However, potential details might be lost during the computational processing of SqueezeSeg and other similar kinds of networks. In this work, we try to retain the detailed information of the image by combining PointSeg network and the conditional random field in order to capture more data information and improve the recall rate. These two processes can complement and fully play their respective advantages. The proposed method has been tested on KITTI dataset. Simulation results demonstrate that our method can overcome the shortcomings of the SqueezeSeg network and similar kinds of networks on the extraction of detailed information.
AB - Point cloud image segmentation plays an important role in self-driving. SqueezeSeg network has good performance in terms of accuracy and calculation speed on point cloud segmentation. However, potential details might be lost during the computational processing of SqueezeSeg and other similar kinds of networks. In this work, we try to retain the detailed information of the image by combining PointSeg network and the conditional random field in order to capture more data information and improve the recall rate. These two processes can complement and fully play their respective advantages. The proposed method has been tested on KITTI dataset. Simulation results demonstrate that our method can overcome the shortcomings of the SqueezeSeg network and similar kinds of networks on the extraction of detailed information.
KW - conditional random field
KW - convolution neural network
KW - point cloud
KW - semantic segmentation
UR - https://www.scopus.com/pages/publications/85080900624
U2 - 10.1109/SSCI44817.2019.9002818
DO - 10.1109/SSCI44817.2019.9002818
M3 - 会议稿件
AN - SCOPUS:85080900624
T3 - 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019
SP - 1214
EP - 1218
BT - 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Symposium Series on Computational Intelligence, SSCI 2019
Y2 - 6 December 2019 through 9 December 2019
ER -