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Noha Radwan

Publications

PhD Thesis

  • Noha Radwan
    Leveraging Sparse and Dense Features for Reliable State Estimation in Urban Environments
    PhD Thesis, University of Freiburg, Department of Computer Science, 2019
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Preprints

  • Noha Radwan, Abhinav Valada and Wolfram Burgard
    Multimodal Interaction-aware Motion Prediction for Autonomous Street Crossing arXiv preprint arXiv:1808.06887, 2018
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Journal Articles

  • Noha Radwan*, Abhinav Valada* and Wolfram Burgard
    VLocNet++: Deep Multitask Learning for Semantic Visual Localization and Odometry
    IEEE Robotics and Automation Letters (RA-L), September 2018.
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Conference Papers

  • Abhinav Valada*, Noha Radwan* and Wolfram Burgard
    Deep Auxiliary Learning for Visual Localization and Odometry
    Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia, 2018
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  • Gabriel Oliveira*, Noha Radwan*, Wolfram Burgard and Thomas Brox
    Topometric Localization with Deep Learning
    Proceedings of the International Symposium on Robotics Research (ISRR), Puerto Varas, Chile, 2017
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  • Wolfram Burgard, Abhinav Valada, Noha Radwan, Tayyab Naseer, Jingwei Zhang, Johan Vertens, Oier Mees, Andreas Eitel and Gabriel Oliveira
    Perspectives on Deep Multimodal Robot Learning
    Proceedings of the International Symposium on Robotics Research (ISRR), Puerto Varas, Chile, 2017
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  • Noha Radwan, Wera Winterhalter, Christian Dornhege, Wolfram Burgard
    Why Did the Robot Cross the Road? - Learning from Multi-Modal Sensor Data for Autonomous Road Crossing
    Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada, 2017
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  • Noha Radwan, Gian Diego Tipaldi, Luciano Spinello, Wolfram Burgard
    Do you see the Bakery? Leveraging Geo-Referenced Texts for Global Localization in Public Maps
    Proceedings of the IEEE Int. Conf. on Robotics and Automation (ICRA), Stockholm, Sweden, 2016
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Workshop Papers

  • Noha Radwan and Wolfram Burgard
    Multitask Learning for Reliable State Estimation
    RSS Pioneers at Robotics: Science and Systems (RSS), Freiburg, Germany, 2019
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  • Noha Radwan and Wolfram Burgard
    Effective Interaction-aware Trajectory Prediction using Temporal Convolutional Neural Networks
    Proceedings of the Workshop on Crowd Navigation: Current Challenges and New Paradigms for Safe Robot Navigation in Dense Crowds at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 2018
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  • Abhinav Valada*, Noha Radwan* and Wolfram Burgard
    Incorporating Semantic and Geometric Priors in Deep Pose Regression
    Proceedings of the Workshop on Learning and Inference in Robotics: Integrating Structure, Priors and Models at Robotics: Science and Systems (RSS), Pittsburgh, USA, 2018
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