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.
An effective ensemble learning framework for affective behaviour analysis,
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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.