Jozef van Eenbergen

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About

Jozef van Eenbergen is a robotics researcher whose work tackles one of the field’s most stubborn perception challenges: enabling robots to see and understand transparent objects. Standard 3D sensors fail dramatically on glass, plastic, and other clear materials because light refracts and absorbs rather than reflects cleanly. Van Eenbergen’s key contribution is the **RGB-D Local Implicit Function**, a novel deep-learning approach that fuses color and noisy depth data to complete the missing depth information for transparent objects. This method, detailed in his highly cited 2021 paper (85 citations), allows robots to perceive the full 3D geometry of transparent surfaces—a critical capability for manipulation tasks in domestic and industrial settings. By bridging the gap between RGB-D sensing and implicit neural representations, his work directly addresses a long-standing bottleneck in robotic perception. The impact of this research is evident in its rapid adoption by the computer vision and robotics communities, where it has become a foundational reference for subsequent work on transparent object reconstruction. Van Eenbergen’s contributions are paving the way for more robust, real-world robotic systems that can handle the complex, everyday objects that traditional sensors miss.