DSNet for Real-Time Driving Scene Semantic Segmentation

Understand

We focus on the very challenging task of semantic segmentation for autonomous driving system.

• It must deliver decent semantic segmentation result for traffic critical objects real-time.
• In this paper, we propose a very efficient yet powerful deep neural network for driving scene semantic segmentation termed as Driving Segmentation Network (DSNet).
• DSNet achieves state-of-the-art balance between accuracy and inference speed through efficient units and architecture design inspired by ShuffleNet V2 and ENet.