Fast real-time semantic segmentation for autonomous driving

He Sun

doi:10.1117/12.2681368

8 June 2023 Fast real-time semantic segmentation for autonomous driving

He Sun

Proceedings Volume 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023); 127073S (2023) https://doi.org/10.1117/12.2681368
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 2023, Changsha, China

Abstract

Semantic segmentation for autonomous driving has high-speed requirements, but the current semantic segmentation model requires a lot of computing resources and is very time-consuming, which makes it less suitable for autonomous driving. To solve this problem, we propose a fast real-time semantic segmentation network, which has a minimal amount of computing and can run in real-time, so it is very suitable for the self-driving field. The framework contains two essential modules, FPN of images and shallow Backbone. It ensures the efficiency of image multi-scale features and feature extraction, respectively. Experimental results on cityscapes show the effectiveness of our method.

Citation Download Citation

He Sun "Fast real-time semantic segmentation for autonomous driving", Proc. SPIE 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 127073S (8 June 2023); https://doi.org/10.1117/12.2681368

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