Nowadays, and more than a decade after the first steps towards autonomous driving, we
keep heading to achieve fully autonomous vehicles on our roads, with LiDAR sensors being …

In this paper, we present RegNet, the first deep convolutional neural network (CNN) to infer
a 6 degrees of freedom (DOF) extrinsic calibration between multimodal sensors, exemplified …

The recent trend of fusing complementary data from LiDARs and cameras for more accurate
perception has made the extrinsic calibration between the two sensors critically important …

Accurate LiDAR-camera online calibration is critical for modern autonomous vehicles and
robot platforms. Dominant methods heavily rely on hand-crafted features, which are not …

Optoelectronic sensing systems are used in automated vehicles for in-cabin features such
as driver attention and distraction monitoring. As automated driving technology continues to …

Mobile light detection and ranging (LiDAR) systems are widely used to generate precise 3-D
spatial information, which in turn aids a variety of applications such as digital building model …

As a crucial step of sensor data fusion, sensor calibration plays a vital role in many cutting-
edge machine vision applications, such as autonomous vehicles and AR/VR. Existing …

We present a new method for joint automatic extrinsic calibration and sensor fusion for a
multimodal sensor system comprising a LIDAR and an optical camera. Our approach …

We address the problem of 3D reconstruction from uncalibrated LiDAR point cloud and
stereo images. Since the usage of each sensor alone for 3D reconstruction has weaknesses …

In this paper, we introduce a novel approach to estimate the extrinsic parameters between a
LiDAR and a camera. Our method is based on line correspondences between the LiDAR …