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

Here’s what our customers say about us

“We were very impressed with Playment’s ability to grasp complex requirements and quickly build custom tools to support it. Our dedicated engagement manager was very helpful in sharing his domain expertise to formulate the right solution for our team.”
Nikola Noxon
Senior Engineer, Daimler
“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
“Playment's quality annotations helped us focus our efforts towards building perception system for our robots. Their flexibility to seamlessly incorporate our feedback and evolving requirements have made them a trusted partner.”
Jack Guo
Software Engineer, Nuro
“Quality annotations by Playment have helped us achieve higher accuracy of our models in a very short time. Flexible solutions, QA process, and dedicated project manager helped us have peace of mind. The team was able to experience a real off-loading of annotation needs.”
Abhishek Gupta
Machine Learning Specialist, HELLA India Automotive
Playment's labeling customer: aimotive logo
Playment's labeling customer: didi logo
Playment's labeling customer: ouster logo
Playment's labeling customer: starsky logo
Playment's labeling customer: nuro logo
Playment's labeling customer: hella logo
Playment's labeling customer: daimler logo
Playment's labeling customer: samsung logo
Playment's labeling customer: vayavision logo
Playment's labeling customer: continental logo
Playment's labeling customer: alibaba logo
Playment's labeling customer: saic logo
Playment's labeling customer: aimotive logo
Playment's labeling customer: didi logo
Playment's labeling customer: ouster logo
Playment's labeling customer: starsky logo
Playment's labeling customer: nuro logo
Playment's labeling customer: hella logo

We make the labeling process simple

Easy project set up with GT Manage
Project Setup

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

Raw dataset transferred via APIs
Raw Dataset

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

Easy project set up with GT Manage
Project Setup

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

Human in the loop using GT Studio
Human in the Loop

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

QC tools for maintaining quality
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.

High-quality datasets delivered to customers
Export Results

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