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Real-time 3D Facial Tracking via Cascaded Compositional Learning
[article]
2020
arXiv
pre-print
We propose to learn a cascade of globally-optimized modular boosted ferns (GoMBF) to solve multi-modal facial motion regression for real-time 3D facial tracking from a monocular RGB camera. GoMBF is a deep composition of multiple regression models with each is a boosted ferns initially trained to predict partial motion parameters of the same modality, and then concatenated together via a global optimization step to form a singular strong boosted ferns that can effectively handle the whole
arXiv:2009.00935v1
fatcat:qqk5cmxcfjh4bjnwspotwge7oy