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 …

This paper proposes SemCal: an automatic, tar-getless, extrinsic calibration algorithm for a
LiDAR and camera system using semantic information. We leverage a neural information …

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 …

LiDAR-Camera online calibration is of great significance for building a stable autonomous
driving perception system. For online calibration, a key challenge lies in constructing a …

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 …

The integration of multiple cameras and 3D Li-DARs has become basic configuration of
augmented reality devices, robotics, and autonomous vehicles. The calibration of multi …

Accurate LiDAR-camera extrinsic calibration is a precondition for many multi-sensor systems
in mobile robots. Most calibration methods rely on laborious manual operations and …

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 …

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 …

For autonomous vehicles, an accurate calibration for LiDAR and camera is a prerequisite for
multi-sensor perception systems. However, existing calibration techniques require either a …