Radar Fields: An Extension of Radiance Fields to SAR

Thibaud Ehret, Roger Mari, Dawa Derksen, Nicolas Gasnier, Gabriele Facciolo; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024, pp. 564-574

Radiance fields have been a major breakthrough in the field of inverse rendering novel view synthesis and 3D modeling of complex scenes from multi-view image collections. Since their introduction it was shown that they could be extended to other modalities such as LiDAR radio frequencies X-ray or ultrasound. In this paper we show that despite the important difference between optical and synthetic aperture radar (SAR) image formation models it is possible to extend radiance fields to radar images thus presenting the first "radar fields". This allows us to learn surface models using only collections of radar images similar to how regular radiance fields are learned and with the same computational complexity on average. Thanks to similarities in how both fields are defined this work also shows a potential for hybrid methods combining both optical and SAR images.