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Spatio-Temporal Relation and Attention Learning for Facial Action Unit Detection
[article]
2020
arXiv
pre-print
Spatio-temporal relations among facial action units (AUs) convey significant information for AU detection yet have not been thoroughly exploited. The main reasons are the limited capability of current AU detection works in simultaneously learning spatial and temporal relations, and the lack of precise localization information for AU feature learning. To tackle these limitations, we propose a novel spatio-temporal relation and attention learning framework for AU detection. Specifically, we
arXiv:2001.01168v1
fatcat:zsvic45l7jcjnpekqwyrnldj5q