  In the typical urban intersection scenario, both vehicles and infrastructures
are equipped with visual and LiDAR sensors. By successfully integrating the
data from vehicle-side and road monitoring devices, a more comprehensive and
accurate environmental perception and information acquisition can be achieved.
The Calibration of sensors, as an essential component of autonomous driving
technology, has consistently drawn significant attention. Particularly in
scenarios involving multiple sensors collaboratively perceiving and addressing
localization challenges, the requirement for inter-sensor calibration becomes
crucial. Recent years have witnessed the emergence of the concept of multi-end
cooperation, where infrastructure captures and transmits surrounding
environment information to vehicles, bolstering their perception capabilities
while mitigating costs. However, this also poses technical complexities,
underscoring the pressing need for diverse end calibration. Camera and LiDAR,
the bedrock sensors in autonomous driving, exhibit expansive applicability.
This paper comprehensively examines and analyzes the calibration of multi-end
camera-LiDAR setups from vehicle, roadside, and vehicle-road cooperation
perspectives, outlining their relevant applications and profound significance.
Concluding with a summary, we present our future-oriented ideas and hypotheses.
