ResLPR

Given the lack of LiDAR-based place recognition (LPR) datasets under adverse weather, we introduce ResLPR, a novel benchmark that examines SOTA LPR methods under a wide range of LiDAR distortions induced by severe snow, fog, and rain conditions.

Specifically, we constructed the WeatherKITTI and WeatherNCLT datasets based on the widely used LPR datasets KITTI and NCLT, utilizing the simulation methods based on physical principles and engineering experience.