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There and Back Again: Learning to Simulate Radar Data for Real-World Applications
Here we propose to learn a radar sensor model capable of synthesising faithful radar observations based on simulated elevation maps.
Masking by Moving: Learning Distraction-Free Radar Odometry from Pose Information
This paper presents an end-to-end radar odometry system which delivers robust, real-time pose estimates based on a learned embedding space free of sensing artefacts and distractor objects.
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