Domain-Adaptive Self-Supervised Pre-Training for Face & Body Detection in Drawings

This work shows how self-supervised learning, based on a teacher-student network with a modified student network update design, can be used to build face and body detectors and demonstrates that style transfer can be incorporated into the learning pipeline to bootstrap detectors using a vast amount of out-of-domain labeled images from natural images.