Instance Aware Segmentation for Autonomous Vehicles

Ultra-precise detection and localization for highly dynamic environments. Detect street lights, headlights to save and efficiently utilize energy.

Instance Aware Segmentation for Autonomous Vehicles

Instance Aware Segmentation for Autonomous Vehicles

Annotations

Semantic Segmentation

Classes

  • Car
  • Pedestrian
  • Bollard
  • Truck
  • Bike
  • Bus
  • Pole
  • Drivable Area
  • Traffic Sign
  • Street Lamp
  • Barrier
  • Building
  • Tree
  • Unknown
  • Traffic Light
  • Others
  • Sky
  • Billboard
  • Guard Rail
  • Bush
  • Terrain
Instance Aware Segmentation for Autonomous Vehicles

Instance Aware Segmentation for Autonomous Vehicles

Annotations

Semantic Segmentation

Classes

  • Car
  • Pedestrian
  • Bollard
  • Truck
  • Bike
  • Bus
  • Pole
  • Drivable Area
  • Traffic Sign
  • Street Lamp
  • Barrier
  • Building
  • Tree
  • Unknown
  • Traffic Light
  • Others
  • Sky
  • Billboard
  • Guard Rail
  • Bush
  • Terrain

We're trusted by

Playment was an outstanding partner for Ever AI. Their skilled staff was able to quickly and accurately tag 100s of thousands of photos for us which greatly improved the accuracy of our face detection and recognition models. Their project managers asked excellent clarifying questions which resulted in a superior project result.
Charles E. Rice
CTO, Ever AI
Playment's fully managed approach has been critical in factoring the variability and scaling up our annotation requirements. Thanks to their tools and skilled workforce, we are extremely satisfied by the quality and turnaround time they have provided. I would highly recommend Playment.
Shmoolik Mangan
Algorithm Development Manager, Vayavision

How It Works?

Project Setup

Our data labeling platform enables project manager to train real people annotate your data and to make sure your models are being trained on high-quality data.

Raw Dataset

Send us dataset and task guidelines. We support API, .CSV, FTP, cloud etc. to source data and setup tasks.

Project Setup

Our data labeling platform enables project manager to train real people annotate your data and to make sure your models are being trained on high-quality data.

Human in the Loop

The semi-automatic labeling process involves combination of deep learning models, hueristics and manual human edits to create high quality annotation at scale.

Rigorous QC

We execute multi-level automated and manual quality checks over each and every annotation. Machine checks to eliminate random or systematic errors combined with human consensus models ensures highly accurate output.

Export Results

Collect all the ground truth dataset you need to train your model.

Contact Us