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Radar Object Detection

The radar object detection (ROD) task aims to classify and localize the objects in 3D purely from radar's radio frequency (RF) images.

Papers

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Showing 1–10 of 29 papers

TitleStatusHype
RADLER: Radar Object Detection Leveraging Semantic 3D City Models and Self-Supervised Radar-Image Learning—0
SpikingRTNH: Spiking Neural Network for 4D Radar Object DetectionCode0
TransRAD: Retentive Vision Transformer for Enhanced Radar Object DetectionCode1
Mask-RadarNet: Enhancing Transformer With Spatial-Temporal Semantic Context for Radar Object Detection in Autonomous Driving—0
SCKD: Semi-Supervised Cross-Modality Knowledge Distillation for 4D Radar Object DetectionCode0
DSFEC: Efficient and Deployable Deep Radar Object Detection—0
MUFASA: Multi-View Fusion and Adaptation Network with Spatial Awareness for Radar Object Detection—0
RadSimReal: Bridging the Gap Between Synthetic and Real Data in Radar Object Detection With Simulation—0
CRKD: Enhanced Camera-Radar Object Detection with Cross-modality Knowledge Distillation—0
Leveraging Self-Supervised Instance Contrastive Learning for Radar Object Detection—0
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