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Deep learning for mmWave radar pointcloud generation

Published on:

27 September 2023

Primary Category:

Image and Video Processing

Paper Authors:

Ruixu Geng,

Yadong Li,

Dongheng Zhang,

Jincheng Wu,

Yating Gao,

Yang Hu,

Yan Chen

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Key Details

Proposes DREAM-PCD framework to generate high-quality mmWave radar pointclouds

Uses multi-frame accumulation to increase density and resolution

Employs 'real-denoise' network to remove noise while improving generalization

Introduces large-scale RadarEyes dataset to advance research

Achieves state-of-the-art performance and real-time capability

AI generated summary

Deep learning for mmWave radar pointcloud generation

This paper proposes a novel framework called DREAM-PCD that combines signal processing and deep learning to address key challenges in generating high-quality pointclouds from mmWave radar. It tackles issues like sparse pointclouds, low resolution, and noise using multi-frame accumulation and a 'real-denoise' network.

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