Computer Vision


The Computer Vision Team at the CAMP Chair mostly focuses its research activity on three topics in the area of 3D scene understanding: reconstruction, object detection & pose estimation and learning on 3D data. Modern 3D reconstruction and SLAM frameworks in combination with Object Detection & Pose Estimation build up the basis for scene understanding. Our objective is to merge deep learning and 3D perception methodologies, providing real-time, robust and scalable learning technology that can be applied on RGB and 3D data. Applications of our research activities are mainly found in the fields of robotic perception and scene understanding, augmented reality, autonomous driving as well as medical image analysis. The team is currently involved in several collaborations with companies and universities around the world, aiming to develop computer vision technology that can be deployed by research teams, companies and start-ups in order to tackle real problems and enable new applications.

Group Members

Benjamin Busam Nikolas Brasch Federico Tombari
Jakob Mayr Shun-Cheng Wu Yanyan Li
Johanna Wald Helisa Dhamo Azade Farshad
Guangyao Zhai Markus Herb Fabian Manhardt
Yan Di Pengyuan Wang Stefano Gasperini
Alexander Lehner Yida Wang Mahdi Saleh
Evin Pınar Örnek Artem Savkin Huseyin Coskun
Hyun Jun Jung Patrick Ruhkamp  


Campus Garching