CS-Wild-Places Dataset

CS-Wild-Places is a large-scale lidar dataset for cross-source place recognition between ground and aerial viewpoints in forest environments. The data was collected from four forests in Brisbane, Australia over ten months, with lidar scans captured by a handheld sensor payload (below canopy) and aerial drone (above canopy). CS-Wild-Places builds upon the Wild-Places dataset by introducing geo-registered aerial submaps covering Karawatha and Venman forests, enabling research into place recognition between challenging viewpoints. We further release ground and aerial data captured in two new forest environments: QCAT and Samford Ecological Research Facility. The aerial data spans 370 hectares in total, and we captured two ground sequences with 3.5km of total traversal, producing a total of ~36k high resolution lidar submaps with accurate 6-DoF poses and timestamps. We release the data in three main configurations: raw (submaps randomly downsampled to 500k points max), and post-processed (submaps voxel-downsampled with 0.8m or 0.4m voxels, ground points removed, with and without normalisation).