Theodora Kontogianni

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About

Theodora Kontogianni is a leading researcher in 3D computer vision, with a focus on interactive and efficient segmentation of point cloud data. Her primary contributions lie in developing methods that allow users to collaborate with deep learning models in real-time, reducing the need for massive, fully-supervised training datasets. Her most-cited work, "Interactive Object Segmentation in 3D Point Clouds" (2023), has already garnered 24 citations, highlighting its impact on advancing human-in-the-loop systems for 3D scene understanding. By enabling iterative refinement of object boundaries directly in 3D space, Kontogianni’s approach addresses a critical bottleneck in autonomous driving, robotics, and augmented reality—where labeled data is scarce and costly. Her earlier 2022 version of this work further laid the groundwork for interactive segmentation, demonstrating sustained interest in her methodology. Kontogianni’s research bridges the gap between user guidance and automated learning, making 3D segmentation more accessible and practical. Her achievements are particularly notable for pushing the boundaries of interactive AI, offering a scalable solution to complex spatial tasks. For students and researchers, her work exemplifies how combining user input with deep learning can unlock new efficiencies in 3D data processing.