Real-time road scene segmentation based on knowledge distillation Real-time road semantic segmentation

Aiming at the problem that it is difficult to balance the accuracy and computational efficiency of the road scene semantic segmentation algorithm, a real-time road scene segmentation algorithm based on knowledge distillation is proposed. The algorithm introduces three key functional modules; (1) using an asymmetric convolutional pyramid module on the top of the encoder; (2) incorporating a coordinate attention module in the network; (3) Using high accuracy non-real time models to distill knowledge on lightweight model. The method in this paper achieves a balance of accuracy and realtime performance on the CamVid dataset. the inference speed is 63.7 FPS and the GFLOPs are 109.2 while the mIoU is 79.3% when computed on an NVIDIA GTX 1080Ti.