RadarTwin produces deployment-specific mmWave radar simulations from 3D models that enable real-object recognition at 2.5 times chance with zero real labels and 95.3% accuracy with few labels on a 12-way task.
InProceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems (SenSys ’25)
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CooperScene provides 59K synchronized frames with 344K 3D annotations from multi-modal sensors on 3 CAVs and 1 RSU plus real C-V2X communication traces for cooperative autonomy benchmarking.
citing papers explorer
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RadarTwin: Scene-Specific mmWave Radar Simulation and Learning for Mobile Indoor Perception
RadarTwin produces deployment-specific mmWave radar simulations from 3D models that enable real-object recognition at 2.5 times chance with zero real labels and 95.3% accuracy with few labels on a 12-way task.
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CooperScene: Multi-Modal Cooperative Autonomy Benchmark with C-V2X Communication Characterization
CooperScene provides 59K synchronized frames with 344K 3D annotations from multi-modal sensors on 3 CAVs and 1 RSU plus real C-V2X communication traces for cooperative autonomy benchmarking.