CS-Campus3D

CrossSource-Campus3D

Introduced in CrossLoc3D: Aerial-Ground Cross-Source 3D Place Recognition2023

About this Dataset

We present CS-Campus3D, the first 3D aerial-ground cross-source dataset consisting of point cloud data from both aerial and ground LiDAR scans. The point clouds in CS-Campus3D have representation gaps and other features like different views, point densities, and noise pattern.

Source: CrossLoc3D: Aerial-Ground Cross-Source 3D Place Recognition

Dataset Variants

CS-Campus3D

Papers1

CrossLoc3D: Aerial-Ground Cross-Source 3D Place Recognition

The CrossLoc3D algorithm achieves performance comparable to state-of-the-art 3D place recognition method on the Oxford RobotCar and presents CS-Campus3D, the first 3D aerial-ground cross-source dataset consisting of point cloud data from both aerial and ground LiDAR scans.

Tasks

EDIT

3D Place Recognition

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Statistics

Papers

1

Tasks

32

Introduced

2023