activity
20172022
most citedChipNet: Real-Time LiDAR Processing for Drivable Region Segmentation on an FPGA

82 citations · 160 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CV2022★ 1 cited

A Near Sensor Edge Computing System for Point Cloud Semantic Segmentation

Lin Bai, Yiming Zhao, Xinming Huang

Point cloud semantic segmentation has attracted attentions due to its robustness to light condition. This makes it an ideal semantic solution for autonomous driving. However, consi…

cs.CV2021

FIDNet: LiDAR Point Cloud Semantic Segmentation with Fully Interpolation Decoding

Yiming Zhao, Lin Bai, Xinming Huang

Projecting the point cloud on the 2D spherical range image transforms the LiDAR semantic segmentation to a 2D segmentation task on the range image. However, the LiDAR range image i…

cs.CV2021

Enabling 3D Object Detection with a Low-Resolution LiDAR

Lin Bai, Yiming Zhao, Xinming Huang

Light Detection And Ranging (LiDAR) has been widely used in autonomous vehicles for perception and localization. However, the cost of a high-resolution LiDAR is still prohibitively…

cs.CV2021★ 41 cited

A Surface Geometry Model for LiDAR Depth Completion

Yiming Zhao, Lin Bai, Ziming Zhang +1

LiDAR depth completion is a task that predicts depth values for every pixel on the corresponding camera frame, although only sparse LiDAR points are available. Most of the existing…

eess.IV2020★ 1 cited

DepthNet: Real-Time LiDAR Point Cloud Depth Completion for Autonomous Vehicles

Lin Bai, Yiming Zhao, Mahdi Elhousni +1

Autonomous vehicles rely heavily on sensors such as camera and LiDAR, which provide real-time information about their surroundings for the tasks of perception, planning and control…

eess.IV2020★ 1 cited

RoadNet-RT: High Throughput CNN Architecture and SoC Design for Real-Time Road Segmentation

Lin Bai, Yecheng Lyu, Xinming Huang

In recent years, convolutional neural network has gained popularity in many engineering applications especially for computer vision. In order to achieve better performance, often m…