Dual Attention Dual-Resolution Networks for Real-Time Semantic Segmentation of Street Scenes
TL;DR
This paper introduces a dual attention dual-resolution network for real-time semantic segmentation in street scenes, aiming to balance accuracy and speed for autonomous driving applications. It addresses the trade-off between computational cost and performance in existing models.
Dual Attention Dual-Resolution Networks for Real-Time Semantic Segmentation of Street Scenes
Baofeng Ye; Renzheng Xue
https://doi.org/10.1109/ACCESS.2024.3521958
Volume 13
Semantic segmentation is a crucial technology for autonomous vehicles to acquire information about their surrounding environment. To ensure that semantic segmentation has practical application value in autonomous driving and robotics, it must achieve corresponding real-time inference speeds. However, existing models either improve accuracy at the cost of high computational expense and long inferen...