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TELUS Digital AI Data Solutions is conducting a data-collection project in France/Guadeloupe to gather neutral selfies, head-pose captures, and historical facial images for machine-learning research and model training. Data variations across lighting, pose, and aging are emphasized to boost accuracy and robustness.
Participants must submit a minimum of 20 valid images to qualify for payment, with a recommended target of 30 images to maximize accepted submissions and QC pass rates.
The objective of this project is to collect a large and diverse dataset of current neutral selfies, head-pose captures, and historical facial images to support machine-learning research and facial recognition model training at TELUS.
The focus is on capturing real-world variation across lighting, poses, expressions, accessories, environments, and aging to improve model accuracy and robustness.
To qualify for payment, you must submit a minimum of 20 valid images. The maximum payout is based on 24 accepted images. Due to the strict automated and manual Quality Control (QC) process, we strongly recommend submitting 30 images to help ensure that enough images remain valid after review
The project compensation rate is $0.55 USD per accepted image.
No specific education is needed to perform the project task.