Wolfgang Fuhl

University of Tübingen, TH Bingen University of Applied Sciences

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About

Wolfgang Fuhl is a leading researcher at the intersection of computer vision, human-robot interaction, and gaze-based machine learning. His work focuses on enabling robots to learn from natural human behavior, particularly through the use of eye-tracking and shared attention. Fuhl’s major contributions include pioneering methods for automatic video annotation and specialized object detection, as demonstrated in his highly cited 2019 paper “MAM: Transfer Learning for Fully Automatic Video Annotation and Specialized Detector Creation” (49 citations). He has also advanced the field of gaze-based object detection, showing that it is possible to detect and localize objects in the wild solely from gaze data—a breakthrough for intuitive human-robot collaboration. His 2023 work on multiperspective teaching of unknown objects via shared-gaze multimodal interaction further extends this paradigm, allowing robots to learn about novel objects through natural human pointing and looking behaviors. With a growing citation impact and a focus on making robot teaching as effortless as human communication, Fuhl’s research is shaping the future of interactive, perceptive robotic systems.