  With the increasing demand for intelligent services of online video
platforms, video character search task has attracted wide attention to support
downstream applications like fine-grained retrieval and summarization. However,
traditional solutions only focus on visual or coarse-grained social information
and thus cannot perform well when facing complex scenes, such as changing
camera view or character posture. Along this line, we leverage social
information and scene context as prior knowledge to solve the problem of
character search in complex scenes. Specifically, we propose a
scene-prior-enhanced framework, named SoCoSearch. We first integrate multimodal
clues for scene context to estimate the prior probability of social
relationships, and then capture characters' co-occurrence to generate an
enhanced social context graph. Afterwards, we design a social context-aware GCN
framework to achieve feature passing between characters to obtain robust
representation for the character search task. Extensive experiments have
validated the effectiveness of SoCoSearch in various metrics.
