The dataset is consisted of HD map dataset & localization dataset
NAVER LABS mapping technology is based on the integration of city-scale aerial photographs with data from a mobile mapping system. We extract information about the layout of the road surface (3D Road Layout) from aerial images. Then we integrate it with 3D point cloud collected by R1, our lightweight mobile mapping system (MMS). Compared to conventional HD maps constructed by MMS vehicles, our mapping process can significantly reduce the production costs and time. We also provide a separate localization dataset containing sensor data and pseudo ground truth poses which can be used for evaluation purposes.
Our HD map dataset consists of the following three components:
We provide the 3D layout of the road surface that we extract from aerial photographs. It contains information regarding the types and precise 3D locations of visual structures on the road surface that are essential for self-driving vehicles, such as lanes, road markings, crosswalks, crossroads and speed bumps.
Our HD map dataset also includes 3D LiDAR point cloud of the surrounding road environment captured from our MMS vehicle. Each point is associated with a semantic label indicating the type of object or region it belongs to. Dynamic objects like vehicles and pedestrians are automatically detected and removed from the point cloud.
Final component of our HD map dataset is a set of visual features extracted from salient regions of the road environment. Obtained by a deep learning model trained in-house, these features are compact, discriminative, and invariant across different viewing conditions, allowing for reliable matching and localization.
|Data||File Type||Dimension||Classes||QuadTile Size||Path Format|
|3D Road Layout||GeoJSON||[x,y,z, type]||Lane, Stop, Link, Sign, ...||-||
|LiDAR Feature Data||LAS||[x,y,z, intensity, classification]||Road / Pole / Other||20.48m x 20.48m x Areal UTM||
|Visual Feature Data||H5||[x,y,z, roll, pitch, yaw, feature_descriptor]||128D Feature Descriptor||20.48m x 20.48m x Areal UTM||
It is important to accurately estimate the current location of the vehicle in autonomous driving situations. The localization technology of NAVER LABS utilizes diverse sensors such as LiDAR, Cameras, GPS, IMU and Wheel Encoders. The localization dataset provides a collection of raw data from these sensors and corresponding pseudo ground truth poses for the purpose of evaluating your own localization algorithms.
|Meta Data||Sensor Data|
|Calibration||Camera||3D / 2D-LiDAR||GPS / INS||FOG||OBD||Wheel Encoder|