Dynamic LiDAR Re-simulation using Compositional Neural Fields

Hanfeng Wu, Xingxing Zuo, Stefan Leutenegger +3

We introduce DyNFL, a novel neural field-based approach for high-fidelity re-simulation of LiDAR scans in dynamic driving scenes. DyNFL processes LiDAR measurements from dynamic en…