Search Results for author:
Found 6 papers, 3 papers with code
Joint object detection and re-identification for 3D obstacle multi-camera systems
In recent years, the field of autonomous driving has witnessed remarkable advancements, driven by the integration of a multitude of sensors, including cameras and LiDAR systems, in different prototypes.
Cycle and Semantic Consistent Adversarial Domain Adaptation for Reducing Simulation-to-Real Domain Shift in LiDAR Bird's Eye View
The performance of object detection methods based on LiDAR information is heavily impacted by the availability of training data, usually limited to certain laser devices.
Automatic Extrinsic Calibration Method for LiDAR and Camera Sensor Setups
Most sensor setups for onboard autonomous perception are composed of LiDARs and vision systems, as they provide complementary information that improves the reliability of the different algorithms necessary to obtain a robust scene understanding.
Towards Autonomous Driving: a Multi-Modal 360$^{\circ}$ Perception Proposal
In this paper, a multi-modal 360$^{\circ}$ framework for 3D object detection and tracking for autonomous vehicles is presented.
BirdNet+: End-to-End 3D Object Detection in LiDAR Bird's Eye View
On-board 3D object detection in autonomous vehicles often relies on geometry information captured by LiDAR devices.
Automatic Extrinsic Calibration for Lidar-Stereo Vehicle Sensor Setups
Sensor setups consisting of a combination of 3D range scanner lasers and stereo vision systems are becoming a popular choice for on-board perception systems in vehicles; however, the combined use of both sources of information implies a tedious calibration process.
