Autonomous Vehicle Annotation
From highways to city streets, we structure the raw data that self-driving cars rely on, accurately, frame by frame, point by point.
Annotation That Powers Self-Driving Systems
Self-driving vehicles rely on more than just cameras; they see through LiDAR, radar, GPS, and high-resolution video, all working together to interpret the road. But this raw data means nothing without structure. We bring order to the chaos by labeling what matters: objects, lanes, signs, movement, and road conditions.
Our autonomous vehicle annotation services help build training datasets that teach perception systems to detect, classify, and respond in real time. Whether it’s navigating highways or city streets, we ensure your data reflects the real world with precision.
Reliable Data Annotation for Agricultural Use Cases
Autonomous driving datasets require more than just bounding boxes. At Pixel Annotation, we specialize in high-volume, high-complexity annotation across camera feeds, LiDAR scans, radar frames, and sensor fusion inputs.
Here’s how we support every layer of autonomous perception:
- 2D & 3D Bounding Box Annotation: For accurate detection and localization of vehicles, pedestrians, obstacles, and traffic elements.
- Semantic & Instance Segmentation: Pixel-level labeling for roads, sidewalks, vehicles, signs, and more.
- LiDAR Point Cloud Annotation: Object classification and localization in 3D space using dense point cloud data.
- Lane & Road Marking Annotation: Annotating lane lines, crosswalks, arrows, and road edges for navigation.
- Traffic Sign & Signal Annotation: Tagging signs, lights, and symbols for accurate recognition and compliance.
We adapt our workflows to match simulation models, real-world driving footage, and R&D-specific edge cases, without compromising speed or precision.
Our Autonomous Vehicle Annotation Services
We label surrounding vehicles, pedestrians, cyclists, traffic cones, and roadside obstacles, enabling detection and scene understanding.
Using semantic segmentation, we outline drivable areas, bike lanes, curbs, crosswalks, and barriers, building ground truth for navigation and path planning.
We annotate 3D point clouds to identify spatial depth, distance, and object contours, helping AVs understand the road beyond what cameras can see.
We tag stop signs, speed limits, traffic lights, arrows, and surface text to support rule-based navigation and visual compliance in dynamic environments.
Why Choose Pixel Annotation?
In-House Annotators Trained for Every Industry
Transforming complex medical images into precisely labeled data that powers healthcare AI solutions.
Expert-Reviewed Labels Across All Domains
Transforming complex medical images into precisely labeled data that powers healthcare AI solutions.
On-Time Delivery Without Quality Trade-Offs
Transforming complex medical images into precisely labeled data that powers healthcare AI solutions.
Secure Annotation with Full Data Privacy
Transforming complex medical images into precisely labeled data that powers healthcare AI solutions.
Industry Use Cases
We annotate pedestrians and traffic lights from camera feeds to support AV object detection pipelines.
We annotate every object in driving scenes at the pixel level, including vehicles, pedestrians, roads, traffic signs, and surrounding infrastructure.
Get Your Data Annotated by Experts!
Transform your data into powerful insights with our expert annotation services tailored for your specific AI needs and goals.
Our Suite of Data Annotation Tools
Our Suite of Data Annotation Tools
Our Suite of Data Annotation Tools
Client Success Stories
Discover why businesses trust Pixel Annotation for their data annotation needs. Our clients share their experiences and insights, highlighting the quality, reliability, and support they receive from our team. Explore how we have become a valued partner in their AI development journey.
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