Search Results for author: Carlos Guindel

Found 6 papers, 4 papers with code

Automatic Extrinsic Calibration for Lidar-Stereo Vehicle Sensor Setups

2 code implementations11 May 2017 Carlos Guindel, Jorge Beltrán, David Martín, Fernando García

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.

Automatic Extrinsic Calibration Method for LiDAR and Camera Sensor Setups

2 code implementations12 Jan 2021 Jorge Beltrán, Carlos Guindel, Arturo de la Escalera, Fernando García

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.

Scene Understanding

BirdNet: a 3D Object Detection Framework from LiDAR information

2 code implementations3 May 2018 Jorge Beltran, Carlos Guindel, Francisco Miguel Moreno, Daniel Cruzado, Fernando Garcia, Arturo de la Escalera

Understanding driving situations regardless the conditions of the traffic scene is a cornerstone on the path towards autonomous vehicles; however, despite common sensor setups already include complementary devices such as LiDAR or radar, most of the research on perception systems has traditionally focused on computer vision.

3D Object Detection Autonomous Vehicles +2

BirdNet+: End-to-End 3D Object Detection in LiDAR Bird's Eye View

2 code implementations9 Mar 2020 Alejandro Barrera, Carlos Guindel, Jorge Beltrán, Fernando García

On-board 3D object detection in autonomous vehicles often relies on geometry information captured by LiDAR devices.

3D Object Detection Autonomous Vehicles +2

Cycle and Semantic Consistent Adversarial Domain Adaptation for Reducing Simulation-to-Real Domain Shift in LiDAR Bird's Eye View

no code implementations22 Apr 2021 Alejandro Barrera, Jorge Beltrán, Carlos Guindel, Jose Antonio Iglesias, Fernando García

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.

3D Object Detection Domain Adaptation +2

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