Face Deduplication Collection
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.
Tasks
The focus is on capturing real-world variation across lighting, poses, expressions, accessories, environments, and aging to improve model accuracy and robustness. The collection includes:
Requirements
• Current Neutral Selfies – clean frontal selfies serving as high-quality identity references, with natural variation in appearance and surroundings.
• Current Head-Pose Captures – selfies captured in assigned head directions to introduce pose variation.
• Historical Images – older photos from participants’ galleries to capture natural aging and long-term appearance changes.
No specific education is needed to perform the project task.
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
Total earnings while participating in this project would be $13.20 USD.
No specific education required; must submit a minimum of 20 valid images to qualify for payment; maximum payout based on 24 accepted images; strict QC process.
Key Responsibilities
- collecting selfies
- capturing head poses
- submitting images
Job Details
- Category: Data and Analytics
- Seniority: No Prior Experience Required
- Commitment: Contract
- Workplace: Remote — London, England, United Kingdom
- Salary: USD 27,456 – 27,456 / year
- Languages: English
About TELUS Digital
A digital company collecting diverse facial image datasets to support machine-learning research and facial recognition model training. — Industry: Information Technology