Jan-Marcel Kezmann
Papers
1
Total Citations
2
H-Index
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About
Jan-Marcel Kezmann is a researcher advancing the field of autonomous perception through efficient 3D object detection. His primary research areas include light-weight prediction quality estimation for object detection in LiDAR point clouds, with a focus on enabling real-time, resource-constrained systems. Kezmann’s major contribution is the development of LMD (Light-weight Model for Detection quality), a novel framework that estimates the reliability of object detection outputs without heavy computational overhead, addressing a critical gap in safety-critical applications like autonomous driving. His work demonstrates how to balance accuracy and efficiency, achieving state-of-the-art performance on benchmark datasets while reducing model complexity. With his 2024 paper “LMD: Light-Weight Prediction Quality Estimation for Object Detection in Lidar Point Clouds” already garnering early citations, Kezmann is establishing a reputation for practical, deployable solutions. His research has direct implications for improving the trustworthiness of perception systems, making him a rising voice in the intersection of computer vision and robotics.
Research Focus
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Top Papers
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