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Found 8 papers, 7 papers with code
OASim: an Open and Adaptive Simulator based on Neural Rendering for Autonomous Driving
With the development of implicit rendering technology and in-depth research on using generative models to produce data at scale, we propose OASim, an open and adaptive simulator and autonomous driving data generator based on implicit neural rendering.
Realistic Rainy Weather Simulation for LiDARs in CARLA Simulator
To this end, we propose a simulator-based physical modeling approach to augment LiDAR data in rainy weather in order to improve the perception performance of LiDAR in this scenario.
Calib-Anything: Zero-training LiDAR-Camera Extrinsic Calibration Method Using Segment Anything
The research on extrinsic calibration between Light Detection and Ranging(LiDAR) and camera are being promoted to a more accurate, automatic and generic manner.
SensorX2car: Sensors-to-car calibration for autonomous driving in road scenarios
However, most prior methods focus on extrinsic calibration between sensors, and few focus on the misalignment between the sensors and the vehicle coordinate system.
Online LiDAR-Camera Extrinsic Parameters Self-checking
This calibration task is multi-modal, where the rich color and texture information captured by the camera and the accurate three-dimensional spatial information from the LiDAR is incredibly significant for downstream tasks.
OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous Driving
To this end, we present OpenCalib, a calibration toolbox that contains a rich set of various sensor calibration methods.
CROON: Automatic Multi-LiDAR Calibration and Refinement Method in Road Scene
Sensor-based environmental perception is a crucial part of the autonomous driving system.
CRLF: Automatic Calibration and Refinement based on Line Feature for LiDAR and Camera in Road Scenes
For autonomous vehicles, an accurate calibration for LiDAR and camera is a prerequisite for multi-sensor perception systems.
