most citedSNE-RoadSeg: Incorporating Surface Normal Information into Semantic Segmentation for Accurate Freespace Detection

185 citations · 350 across the 4 of their papers we have counts for

collaborators

8 papers

cs.RO2021

End-to-End Interactive Prediction and Planning with Optical Flow Distillation for Autonomous Driving

Hengli Wang, Peide Cai, Rui Fan +2

With the recent advancement of deep learning technology, data-driven approaches for autonomous car prediction and planning have achieved extraordinary performance. Nevertheless, mo…

cs.CV202186 cited

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…

cs.RO202079 cited

Learning Collision-Free Space Detection from Stereo Images: Homography Matrix Brings Better Data Augmentation

Rui Fan, Hengli Wang, Peide Cai +4

Collision-free space detection is a critical component of autonomous vehicle perception. The state-of-the-art algorithms are typically based on supervised learning. The performance…

cs.CV2020185 cited

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…

cs.RO2020

Probabilistic End-to-End Vehicle Navigation in Complex Dynamic Environments with Multimodal Sensor Fusion

Peide Cai, Sukai Wang, Yuxiang Sun +1

All-day and all-weather navigation is a critical capability for autonomous driving, which requires proper reaction to varied environmental conditions and complex agent behaviors. R…

cs.CV2020

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…