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 …

In this paper, we present Calibration Recurrent Convolutional Neural Network (CalibRCNN)
to infer a 6 degrees of freedom (DOF) rigid body transformation between 3D LiDAR and 2D …

There is no denying the fact that LiDAR-camera online calibration is an extremely complex
problem. For automatic driving technology development, a stable, accurate, and fast online …

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 …

Multi-sensor fusion is for enhancing environment perception and 3D reconstruction in self-
driving and robot navigation. Calibration between sensors is the precondition of effective …

As an essential procedure of data fusion, LiDAR-camera calibration is critical for
autonomous vehicles and robot navigation. Most calibration methods require laborious …

Due to the difference of data modalities, it'sa very challenging task to find the feature
correspondences between 2D and 3D data in LiDAR-Camera calibration. In existing works …

We propose a robust calibration pipeline that optimises the selection of calibration samples
for the estimation of calibration parameters that fit the entire scene. We minimise user error …

Sensor-based environmental perception is a crucial step for autonomous driving systems,
for which an accurate calibration between multiple sensors plays a critical role. For the …

Reliable real-time extrinsic parameters of 3D Light Detection and Ranging (LiDAR) and
camera are a key component of multi-modal perception systems. However, extrinsic …