High quality open-source dataset for autonomous driving
The full PandaSet will be available for download soon.
PandaSet aims to promote and advance research and development in autonomous driving and machine learning.
Combining Hesai’s best in class LiDAR sensors with Scale’s high-quality data annotation, PandaSet is the first public dataset to feature solid-state LiDAR (PandarGT) and point cloud segmentation (Sensor Fusion Segmentation).
It features:
For PandaSet we carefully planned routes and selected scenes that would showcase complex urban driving scenarios, including steep hills, construction, dense traffic and pedestrians, and a variety of times of day and lighting conditions in the morning, afternoon, dusk and evening.
Pandaset scenes are selected from 2 routes in Silicon Valley: (1) San Francisco; and (2) El Camino Real from Palo Alto to San Mateo.
We collected data using a Chrysler Pacifica minivan mounted with a suite of cameras and Hesai LiDARs. Please refer to the figure below for the sensor configuration used for PandaSet.
To achieve a high quality multi-sensor dataset, it is essential to calibrate the extrinsics and intrinsics of every sensor. We express extrinsic coordinates relative to the ego frame, i.e. the midpoint of the rear vehicle axle. The most relevant steps are described below:
Scale’s data annotation platform combines human work and review with smart tools, statistical confidence checks and machine learning checks to ensure the quality of annotations.
The resulting accuracy is consistently higher than what a human or synthetic labeling approach can achieve independently as measured against seven rigorous quality areas for each annotation.
PandaSet includes 3D Bounding boxes for 28 object classes and a rich set of class attributes related to activity, visibility, location, pose. The dataset also includes Point Cloud Segmentation with 37 semantic labels including for smoke, car exhaust, vegetation, and driveable surface.
For detailed definitions of each class and example images, please see the annotation instructions.
Scale’s mission is to accelerate the development of AI by democratizing access to intelligent data.
Scale’s suite of managed labeling services such as Sensor Fusion Annotation, Video Annotation, 2D Box Annotation, 3D Cuboid Annotation, Semantic Segmentation, and Categorization combine manual labeling with best in class tools and machine driven checks to yield stunningly accurate training data.
Hesai Technology is the global leader in 3D-sensors (LiDAR).
Founded in Silicon Valley and headquartered in Shanghai, Hesai’s team of 400+ has created a suite of innovative sensor solutions that combine three core strengths: industry-leading performance, manufacturability, and reliability.
Hesai’s proprietary micro-mirror and waveform fingerprint technologies continue to lead the market in sensor innovation, leading to 200+ patents and customers spanning 18 countries and 42 cities.
The full PandaSet will be available for download soon.