Face Deduplication Collection

This project involves collecting a diverse dataset of current neutral selfies, head-pose captures, and historical facial images to support machine-learning research and facial recognition model training. The focus is on capturing real-world variation across lighting, poses, expressions, accessories, environments, and aging to improve model accuracy and robustness. Participants must submit a minimum of 20 valid images to qualify for payment, with compensation based on accepted images.