Lukas Reisinger
Papers
1
Total Citations
4
H-Index
1
About
Lukas Reisinger is a researcher in computer vision and robotics, with a focus on 3D perception and synthetic data generation. His primary contributions lie in developing methods for robust object detection and pose estimation in industrial settings, particularly for pallet handling in automated warehouses. His most-cited work, "Pallet Detection and 3D Pose Estimation via Geometric Cues Learned from Synthetic Data" (2025, 4 citations), introduces a novel approach that leverages geometric cues from synthetically generated data to achieve accurate 3D pose estimation without requiring real-world training samples. This work addresses a critical bottleneck in robotics—the scarcity of annotated real-world data—by demonstrating that synthetic data can effectively bridge the sim-to-real gap for geometric reasoning tasks. Reisinger’s research has practical implications for logistics automation, enabling more reliable and cost-effective robotic manipulation. His achievements include advancing the state of the art in synthetic data utilization for industrial computer vision, with potential to reduce deployment costs in manufacturing and warehousing. As a rising voice in the field, his work continues to inspire new directions in learning-based 3D perception.
Research Focus
Key Achievements
Top Papers
- 1