Empowering Automotive
Al with Data
World-class annotation services for Autonomous Driving.
Empowering Automotive
The New Engine of Automotive
Algorithms for autonomous driving use supervised deep learning, which uses known variables and relationships. These Label AI's autonomous driving data solutions support core algorithm training in areas such as environment perception, precise positioning, decision-making and planning, control and execution, high-precision mapping, and vehicle-to-everything (V2X) communication. These solutions provide the data required to unlock the full potential of autonomous driving technology.
Label Al Automotive Solution
Centered around intelligent data platforms, we establish infrastructures supporting largescale intelligent services. Through systematic platform products, we offer a one-stop solution for users' diverse needs regarding Al general underlying infrastructure. This approach allows enterprises to progressively transform their business into individual algorithm models, enabling reuse, innovative combinations, and scalable development of intelligent services while empowering business operations.
Point Cloud Fusion Continuous Frames
Segment different semantic regions like ground, buildings, vehicles, etc., in 3D point cloud data using the polygon tool.
4D Point Cloud Segmentation
In 4D point cloud data with a time dimension, perform detailed semantic and instance segmentation for static scene elements like buildings, road surfaces, and dynamic objects like pedestrians, vehicles. Outline and label each independent object in every frame of point cloud data, maintaining a unique ID for each instance across consecutive frames, generating comprehensive 4D spatiotemporal segmentation information.
3D Point Cloud Segmentation
Segment different semantic regions like ground, buildings, vehicles, etc., in 3D point cloud data using the polygon tool.
Panoramic Segmentation
Utilize the polygon tool to segment each pixel region in the image, providing detailed contour annotations and semantic labeling for all objects in the entire scene.
BEV-Bird's Eye View
Precisely annotate various target objects from a BEV perspective, track their trajectories, add detailed attribute information and motion interaction relationships for each instance.
Lane Markings
Precisely annotate various target objects from a BEV perspective, track their trajectories, add detailed attribute information and motion interaction relationships for each instance.
Parking Slot
Utilize precise 2D boxes to outline vehicle boundaries, employ polylines for marking intricate parking space boundaries and lane line outlines, and enable multi-level annotation of semantic information, including traffic signs and parking space statuses within the scene.
Point Cloud Fusion Continuous Frames
4D Point Cloud Segmentation
3D Point Cloud Segmentation
Panoramic Segmentation
BEV-Bird's Eye View
Lane Markings
Parking Slot
Why Automotive Al teams Choose us
Enhanced Service Ecosystem
Offering an integrated end-to-end solution, effortlessly addressing infrastructure setup challenges for autonomous driving enterprises.
Comprehensive Coverage
Encompassing data collection, management, annotation, training, and the complete lifecycle of data application for models.
Data Security Measures
Backed by dual security sandbox technology and physical isolation techniques, effectively mitigating risks such as data leakage and loss.