3260 papers • 126 benchmarks • 313 datasets
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This paper provides the first dataset built on this holistic conceptualization of social life that is composed of a hierarchical label space of social domains and social relations and contributes the first models to recognize such domains and relations and find superior performance for attribute based features.
This work has proposed a dualglance model for social relationship recognition, where the first glance fixates at the individual pair of interest and the second glance deploys attention mechanism to explore contextual cues.
This work has found that the interplay between these two factors can be effectively modeled by a novel structured knowledge graph with proper message propagation and attention and can be efficiently integrated into the deep neural network architecture to promote social relationship understanding.
A simpler, faster, and more accurate method named graph relational reasoning network (GR2N) for social relation recognition, which considers the paradigm of jointly inferring the relations by constructing a social relation graph.
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