Alexander Krull
Papers
1
Total Citations
38
H-Index
1
About
Alexander Krull is a leading researcher in computer vision, with a primary focus on 3D pose estimation, object detection, and scene understanding. His work is pivotal in bridging the gap between visual perception and real-world interaction, particularly for applications in robotics and augmented reality. Krull’s major contribution lies in developing methods for the accurate pose estimation of complex, articulated objects—such as kinematic chains—which are essential for robots to manipulate tools or interact with dynamic environments. His highly cited 2015 paper, "Pose Estimation of Kinematic Chain Instances via Object Coordinate Regression" (38 citations), introduced a novel approach to regressing object coordinates for precise 3D pose recovery, enabling systems to understand not just static objects but also their movable parts. This work has had a lasting impact on the field, influencing subsequent research in robotic grasping and human-robot interaction. Krull’s research continues to push the boundaries of how machines perceive and interact with the physical world, making him a key figure in advancing practical, vision-driven robotics.
Research Focus
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Top Papers
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