185 citations · 367 across the 8 of their papers we have counts for
5 papers · 1 filter
SNE-RoadSeg+: Rethinking Depth-Normal Translation and Deep Supervision for Freespace Detection
Hengli Wang, Rui Fan, Peide Cai +1
Freespace detection is a fundamental component of autonomous driving perception. Recently, deep convolutional neural networks (DCNNs) have achieved impressive performance for this…
Learning Interpretable End-to-End Vision-Based Motion Planning for Autonomous Driving with Optical Flow Distillation
Hengli Wang, Peide Cai, Yuxiang Sun +2
Recently, deep-learning based approaches have achieved impressive performance for autonomous driving. However, end-to-end vision-based methods typically have limited interpretabili…
PVStereo: Pyramid Voting Module for End-to-End Self-Supervised Stereo Matching
Hengli Wang, Rui Fan, Peide Cai +1
Supervised learning with deep convolutional neural networks (DCNNs) has seen huge adoption in stereo matching. However, the acquisition of large-scale datasets with well-labeled gr…
SNE-RoadSeg: Incorporating Surface Normal Information into Semantic Segmentation for Accurate Freespace Detection
Rui Fan, Hengli Wang, Peide Cai +1
Freespace detection is an essential component of visual perception for self-driving cars. The recent efforts made in data-fusion convolutional neural networks (CNNs) have significa…
VTGNet: A Vision-based Trajectory Generation Network for Autonomous Vehicles in Urban Environments
Peide Cai, Yuxiang Sun, Hengli Wang +1
Traditional methods for autonomous driving are implemented with many building blocks from perception, planning and control, making them difficult to generalize to varied scenarios…