Face Deduplication Collection

SOKIFY PRESENTS: Face Deduplication Collection Project About This Opportunity TELUS Digital is seeking individuals to contribute to an important machine learning initiative by providing facial image data. This project helps train and improve facial recognition models by building a diverse, real-world dataset. Your contributions will support the development of more accurate and robust AI systems. What You'll Be Collecting Your task involves gathering three types of facial images: Current Neutral Selfies - straightforward front-facing photos of yourself in natural lighting and everyday settings. These serve as clear identity reference images. Current Head-Pose Captures - selfies taken from specific head angles and directions as assigned by the project. This variation helps models recognize faces from different perspectives. Historical Images - older photographs from your personal collection that show how your appearance has changed over time. These help train models to recognize aging and natural variations. The images captured will introduce real-world variation in lighting conditions, poses, facial expressions, accessories, surrounding environments, and aging patterns. All these factors are essential for creating AI models that work reliably in actual conditions. What You Need to Know About Payment and Quality Control To receive payment, you must submit a minimum of 20 valid images. The maximum compensation is based on 24 accepted images. Because the project uses both automated and manual quality review processes that are quite rigorous, we recommend submitting approximately 30 images. This buffer helps ensure sufficient images pass quality control and qualify for payment. What We're Looking For There are no specific educational requirements for this project. You simply need to be willing to provide genuine facial image data that meets the collection guidelines. Important: Please register and apply using a Gmail address as your primary account for this project.