@inproceedings{9b5eb53e3f3f401fbcdcf91bf11e7437,
title = "Efficient Light Deep Network for Street Scene Parsing",
abstract = "The semantic segmentation is a dense pixel label pre-diction task, which takes quite a lot of resources and computation cost in most of the time. In our approach, we pay attention to balance the speed and better performance which outperforms the state of the art in speed and accuracy for real-time performance. We come up with the idea of new efficient deep backbone that can extract more semantic details, reduce the computation cost and be easy to deploy at the same time. We call our new backbone as Cascaded Mobile Network, which is proved to be very useful. Our proposed model achieves 72.1 mIOU on the CityScapes val, and 69.5 on CamVid. We achieve good balance between speed and accuracy.",
keywords = "CNN, Deep Learning, Efficient B ackbone, Semantic Segmentation, real-time",
author = "Wang, {Zhe Hui} and Sanyuan Zhao and Jianbing Shen and Zhengchao Lei",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Visual Communications and Image Processing, VCIP 2020 ; Conference date: 01-12-2020 Through 04-12-2020",
year = "2020",
month = dec,
day = "1",
doi = "10.1109/VCIP49819.2020.9301795",
language = "English",
series = "2020 IEEE International Conference on Visual Communications and Image Processing, VCIP 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "42--45",
booktitle = "2020 IEEE International Conference on Visual Communications and Image Processing, VCIP 2020",
address = "United States",
}