CaRaFe: Camera-Radar Radiance Fields for Scene Reconstruction

Radar neural reconstruction methods have recently achieved robust 3D scene occupancy from radar measurements alone, as they provide metric depth and are insensitive to adverse weather and low light. However, while these methods can recover some 3D geometry, their input radar data mixes information across elevation into a 2D range-azimuth measurement. This fundamentally limits their elevation resolution, especially in automotive scenes with limited vertical baselines. Camera images offer the opposite tradeoff: they contain strong, high resolution cues for object elevation but struggle with accurate depth and in adverse conditions.