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Found 4 papers, 1 papers with code
Towards Dense and Accurate Radar Perception Via Efficient Cross-Modal Diffusion Model
Millimeter wave (mmWave) radars have attracted significant attention from both academia and industry due to their capability to operate in extreme weather conditions.
Passive Non-Line-of-Sight Imaging with Light Transport Modulation
In this work, we propose NLOS-LTM, a novel passive NLOS imaging method that effectively handles multiple light transport conditions with a single network.
DREAM-PCD: Deep Reconstruction and Enhancement of mmWave Radar Pointcloud
However, existing methods failed to simultaneously address the three main challenges in mmWave radar pointcloud reconstruction: specular information lost, low angular resolution, and strong interference and noise.
Recent Advances on Non-Line-of-Sight Imaging: Conventional Physical Models, Deep Learning, and New Scenes
As an emerging technology that has attracted huge attention, non-line-of-sight (NLOS) imaging can reconstruct hidden objects by analyzing the diffuse reflection on a relay surface, with broad application prospects in the fields of autonomous driving, medical imaging, and defense.
