• DOI:10.1109/WACV.2018.00145
Corpus ID: 3885961

Driving Scene Perception Network: Real-Time Joint Detection, Depth Estimation and Semantic Segmentation

@article{Chen2018DrivingSP,
  title={Driving Scene Perception Network: Real-Time Joint Detection, Depth Estimation and Semantic Segmentation},
  author={L. Chen and Zeng Yang and J. Ma and Zheng Luo},
  journal={2018 IEEE Winter Conference on Applications of Computer Vision (WACV)},
  year={2018},
  pages={1283-1291}
}

L. Chen, Zeng Yang, +1 author Zheng Luo

Published 2018

Computer Science

2018 IEEE Winter Conference on Applications of Computer Vision (WACV)

As the demand for enabling high-level autonomous driving has increased in recent years and visual perception is one of the critical features to enable fully autonomous driving, in this paper, we introduce an efficient approach for simultaneous object detection, depth estimation and pixel-level semantic segmentation using a shared convolutional architecture. [...] Key Method The proposed network model, which we named Driving Scene Perception Network (DSPNet), uses multi-level feature maps and multi-task learning…Expand Abstract

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