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From the faculty

  • Informatics colloquium 31. 10. Advances in Learning for Robots Perception

    Informatics colloquium 31. 10. 2017, 14:00 lecture hall D2 prof. ing. Jana Košecká, Ph.D., George Mason University, Google Brain, Mountain View, CA, USA Advances in Learning for Robots Perception Abstract: Advancements in robotic navigation, mapping, object search and recognition rest to a large extent on robust, efficient and scalable semantic understanding of the surrounding environment. In recent years we have developed several approaches for capturing geometry and semantics of environment from video, RGB-D data, or just simply a single RGB image, focusing on indoors and outdoors environments elevant for robotics applications. I will demonstrate our work on predicting locations of generic objects in videos acquired by a moving vehicle, for detailed semantic parsing using deep convolutional neural networks (CNNs), object detection and object pose recovery from single RGB image. The applicability of the presented techniques for autonomous driving, service robotics, mapping and augmented reality applications will be discussed.

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