15 citations · 30 across the 9 of their papers we have counts for
15 papers
Understanding the Challenges When 3D Semantic Segmentation Faces Class Imbalanced and OOD Data
Yancheng Pan, Fan Xie, Huijing Zhao
3D semantic segmentation (3DSS) is an essential process in the creation of a safe autonomous driving system. However, deep learning models for 3D semantic segmentation often suffer…
Multi-Task Conditional Imitation Learning for Autonomous Navigation at Crowded Intersections
Zeyu Zhu, Huijing Zhao
In recent years, great efforts have been devoted to deep imitation learning for autonomous driving control, where raw sensory inputs are directly mapped to control actions. However…
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-…
An Image-based Approach of Task-driven Driving Scene Categorization
Shaochi Hu, Hanwei Fan, Biao Gao +2
Categorizing driving scenes via visual perception is a key technology for safe driving and the downstream tasks of autonomous vehicles. Traditional methods infer scene category by…
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…