15 citations · 25 across the 7 of their papers we have counts for
4 papers · 1 filter
An Active and Contrastive Learning Framework for Fine-Grained Off-Road Semantic Segmentation
Biao Gao, Xijun Zhao, Huijing Zhao
Off-road semantic segmentation with fine-grained labels is necessary for autonomous vehicles to understand driving scenes, as the coarse-grained road detection can not satisfy off-…
Fine-Grained Off-Road Semantic Segmentation and Mapping via Contrastive Learning
Biao Gao, Shaochi Hu, Xijun Zhao +1
Road detection or traversability analysis has been a key technique for a mobile robot to traverse complex off-road scenes. The problem has been mainly formulated in early works as…
Are We Hungry for 3D LiDAR Data for Semantic Segmentation? A Survey and Experimental Study
Biao Gao, Yancheng Pan, Chengkun Li +2
3D semantic segmentation is a fundamental task for robotic and autonomous driving applications. Recent works have been focused on using deep learning techniques, whereas developing…
Off-Road Drivable Area Extraction Using 3D LiDAR Data
Biao Gao, Anran Xu, Yancheng Pan +3
We propose a method for off-road drivable area extraction using 3D LiDAR data with the goal of autonomous driving application. A specific deep learning framework is designed to dea…