Stefan Gumhold

Papers

Total Citations

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About

Stefan Gumhold is a leading figure in computer graphics and visual computing, with key research contributions spanning pose estimation, scientific visualization, and geometry processing. His most cited work, "Pose Estimation of Kinematic Chain Instances via Object Coordinate Regression" (2015, 38 citations), introduced a novel framework for accurately estimating the poses of articulated objects—such as robotic arms or drawers—by regressing object coordinates directly from images. This work has significant implications for augmented reality and robotics, enabling machines to interact with complex, moving environments. In another influential study, "Visual Analysis of Trajectories in Multi‐Dimensional State Spaces" (2014, 18 citations), Gumhold advanced the visualization of high-dimensional continuous data by adapting scatterplot techniques to reveal hidden patterns in complex system trajectories. His broader impact is reflected in over 1,500 total citations, with notable achievements including pioneering work on point cloud compression and real-time rendering. As a professor at the University of Stuttgart, Gumhold continues to shape the field through innovative algorithms that bridge the gap between raw data and actionable visual insights, making him a key resource for students and researchers in visual computing.