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arXiv · 2504.12348

3D Object Reconstruction with mmWave Radars

Samah Hussein·Junfeng Guan·Swathi Narashiman·Saurabh Gupta·Haitham Hassanieh
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Abstract

This paper presents RFconstruct, a framework that enables 3D shape reconstruction using commercial off-the-shelf (COTS) mmWave radars for self-driving scenarios. RFconstruct overcomes radar limitations of low angular resolution, specularity, and sparsity in radar point clouds through a holistic system design that addresses hardware, data processing, and machine learning challenges. The first step is fusing data captured by two radar devices that image orthogonal planes, then performing odometry-aware temporal fusion to generate denser 3D point clouds. RFconstruct then reconstructs 3D shapes of objects using a customized encoder-decoder model that does not require prior knowledge of the object's bound box. The shape reconstruction performance of RFconstruct is compared against 3D models extracted from a depth camera equipped with a LiDAR. We show that RFconstruct can accurately generate 3D shapes of cars, bikes, and pedestrians.

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Samah Hussein, Junfeng Guan, Swathi Narashiman, Saurabh Gupta, Haitham Hassanieh. 2025-04-15. 3D Object Reconstruction with mmWave Radars. https://arxiv.org/abs/2504.12348

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