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Decoupled Multi-task Learning with Cyclical Self-Regulation for Face Parsing
[article]
2022
arXiv
pre-print
This paper probes intrinsic factors behind typical failure cases (e.g. spatial inconsistency and boundary confusion) produced by the existing state-of-the-art method in face parsing. To tackle these problems, we propose a novel Decoupled Multi-task Learning with Cyclical Self-Regulation (DML-CSR) for face parsing. Specifically, DML-CSR designs a multi-task model which comprises face parsing, binary edge, and category edge detection. These tasks only share low-level encoder weights without
arXiv:2203.14448v1
fatcat:vyxjnmwranhwtprarxvj2haiui