Lukas Haas

According to our database, Lukas Haas authored at least 14 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

The FACTS Grounding Leaderboard: Benchmarking LLMs' Ability to Ground Responses to Long-Form Input.

Alon Jacovi, Andrew Wang, Chris Alberti, Connie Tao, Jon Lipovetz, Kate Olszewska, Lukas Haas, Michelle Liu, Nate Keating, Adam Bloniarz, Carl Saroufim, Corey Fry, Dror Marcus, Doron Kukliansky, Gaurav Singh Tomar, James Swirhun, Jinwei Xing, Lily Wang, Madhu Gurumurthy, Michael Aaron, Moran Ambar, Rachana Fellinger, Rui Wang, Zizhao Zhang, Sasha Goldshtein, Dipanjan Das

CoRR, January, 2025

2024

Modeling of Motion Distortion Effect of Scanning LiDAR Sensors for Simulation-Based Testing.

Arsalan Haider, Lukas Haas, Shotaro Koyama, Lukas Elster, Michael H. Köhler, Michael Schardt, Thomas Zeh, Hideo Inoue, Martin Jakobi, Alexander W. Koch

IEEE Access, 2024

VelObPoints: a Neural Network for Vehicle Object Detection and Velocity Estimation for Scanning LiDAR Sensors.

Lukas Haas, Nico Leuze, Arsalan Haider, Matthias Kuba, Thomas Zeh, Alfred Schöttl, Martin Jakobi, Alexander W. Koch

Proceedings of the 2024 IEEE SENSORS, Kobe, Japan, October 20-23, 2024, 2024

A Methodology for Verifying and Validating the Functional Performance Evaluation of High-Fidelity RADAR Sensor Models at Raw Data and Detection Levels.

Arsalan Haider, Lukas Haas, Abdulkadir Eryildirim, Thomas Zeh, Shotaro Koyama, Nils Henning Müllner, Martin Jakobi, Alexander W. Koch

Proceedings of the 8th IEEE International Conference on Vision, 2024

PIGEON: Predicting Image Geolocations.

Lukas Haas, Michal Skreta, Silas Alberti, Chelsea Finn

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Velocity Estimation from LiDAR Sensors Motion Distortion Effect.

Lukas Haas, Arsalan Haider, Ludwig Kastner, Thomas Zeh, Tim Poguntke, Matthias Kuba, Michael Schardt, Martin Jakobi, Alexander W. Koch

Sensors, December, 2023

A Methodology to Model the Rain and Fog Effect on the Performance of Automotive LiDAR Sensors.

Arsalan Haider, Marcell Pigniczki, Shotaro Koyama, Michael H. Köhler, Lukas Haas, Maximilian Fink, Michael Schardt, Koji Nagase, Thomas Zeh, Abdulkadir Eryildirim, Tim Poguntke, Hideo Inoue, Martin Jakobi, Alexander W. Koch

Sensors, August, 2023

Performance Evaluation of MEMS-Based Automotive LiDAR Sensor and Its Simulation Model as per ASTM E3125-17 Standard.

Arsalan Haider, Yongjae Cho, Marcell Pigniczki, Michael H. Köhler, Lukas Haas, Ludwig Kastner, Maximilian Fink, Michael Schardt, Yannik Cichy, Shotaro Koyama, Thomas Zeh, Tim Poguntke, Hideo Inoue, Martin Jakobi, Alexander W. Koch

Sensors, March, 2023

PIGEON: Predicting Image Geolocations.

Lukas Haas, Michal Skreta, Silas Alberti

CoRR, 2023

Learning Generalized Zero-Shot Learners for Open-Domain Image Geolocalization.

Lukas Haas, Silas Alberti, Michal Skreta

CoRR, 2023

2022

Development of High-Fidelity Automotive LiDAR Sensor Model with Standardized Interfaces.

Arsalan Haider, Marcell Pigniczki, Michael H. Köhler, Maximilian Fink, Michael Schardt, Yannik Cichy, Thomas Zeh, Lukas Haas, Tim Poguntke, Martin Jakobi, Alexander W. Koch

Sensors, 2022

Estimating Building Energy Efficiency From Street View Imagery, Aerial Imagery, and Land Surface Temperature Data.

Kevin Mayer, Lukas Haas

CoRR, 2022

Untersuchung von Open-Source-Mängelmeldern für den Einsatz in einer Kommunalverwaltung / Evaluation of Open Source Public Service Concerns Reporting Systems.

Lukas Haas, Florian Knoch

AGIT Journal Angew. Geoinformatik, 2022

2016

Robust and Reliable Bionic Optimization of Nonlinear Control Problems.

Lukas Haas, Rolf Steinbuch

Proceedings of the Intelligent Systems Design and Applications, 2016