Spotlight Talks from Selected Extended Abstracts

Unsupervised Place Recognition with Deep Embedding Learning over Radar Videos.
Matthew Gadd, Daniele De Martini, and Paul Newman


Radar-enhanced LiDAR Mapping in Foggy Environments.
Yeong Sang Park, Hyesu Jang, and Ayoung Kim


Improved Radar Localization on Lidar Maps Using Shared Embedding.
Huan Yin, Yue Wang and Rong Xiong


https://github.com/ZJUYH/RaLL

Oriented Surface Points for Efficient and Accurate Radar Odometry.
Daniel Adolfsson, Martin Magnusson, Anas Alhashimi, Achim J. Lilienthal, and Henrik Andreasson


Radar-Inertial State Estimation and Obstacle Detection for Micro-Aerial Vehicles In Dense Fog.
Andrew Kramer and Christoffer Heckman


Radar based Navigation for Autonomous Surface Vehicles.
Ibrahim J. Salman, Justin A. Baum, Hunter J. Damron, Joshua Y. Nelson, Andrew K. Smith, Marios Xanthidis, Joshua Cooper, and Ioannis Rekleitis


[Dataset]
CMU-GPR Dataset: Ground Penetrating Radar Dataset for Robot Localization and Mapping.
Alexander Baikovitz, Paloma Sodhi, Michael Dille, and Michael Kaess


https://github.com/rpl-cmu/CMU-GPR-Dataset

[Dataset]
Radar Data Sets and Machine Learning Algorithms for Automated Driving.
Ole Schumann, Markus Hahn, Nicolas Scheiner, Fabio Weishaupt, Julius F. Tilly, Jurgen Dickmann, and Christian Wohler


https://radar-scenes.com/