3D Point Splatting for mmWave Radar Novel View Synthesis
Researchers propose 3DPS, a differentiable point renderer for mmWave radar novel view synthesis that outperforms optical-NVS baselines by 1.7x-5.2x.
The paper introduces 3D Point Splatting (3DPS), the first differentiable point renderer for radar, derived from the solid-angle form of the radar equation with ITU-R P.2040 material models and complex phasor splatting. On six outdoor ColoRadar scenes it reaches 0.587 mean Pearson correlation on held-out range-azimuth images, between 1.7x and 5.2x the RadarSplat, Radar Fields, and DART baselines. The same optimized scene produces ADC, complex range profile, and RA outputs via standard FFT pipelines, and training takes about 3 minutes per scene on an RTX 4090.
- First differentiable point renderer for radar with explicit material modeling
- Complex-valued output makes the renderer product-agnostic across FFT formats
- Outperforms RadarSplat, Radar Fields, and DART on ColoRadar scenes
- Trains in roughly 3 minutes per scene on a single RTX 4090
- Organizations
- arXiv
From the original article
1 min read at arxiv.orgSolving novel view synthesis (NVS) for millimeter-wave (mmWave) radar requires a renderer that is physically faithful, complex-valued, and multi-viewpoint-tractable. No prior method achieves these three properties simultaneously.
By Adnan Armouti · arxiv.org
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