SSM framework achieves simultaneous state-of-the-art results on AU detection and FE recognition by using textual semantic prototypes and dynamic prior mapping for bidirectional transfer across heterogeneous data.
Spontaneous facial expression analysis based on tem- perature changes and head motions,
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Bidirectional Learning of Facial Action Units and Expressions via Structured Semantic Mapping across Heterogeneous Datasets
SSM framework achieves simultaneous state-of-the-art results on AU detection and FE recognition by using textual semantic prototypes and dynamic prior mapping for bidirectional transfer across heterogeneous data.