  People's social relationships are often manifested through their
surroundings, with certain objects or interactions acting as symbols for
specific relationships, e.g., wedding rings, roses, hugs, or holding hands.
This brings unique challenges to recognizing social relationships, requiring
understanding and capturing the essence of these contexts from visual
appearances. However, current methods of social relationship understanding rely
on the basic classification paradigm of detected persons and objects, which
fails to understand the comprehensive context and often overlooks decisive
social factors, especially subtle visual cues. To highlight the social-aware
context and intricate details, we propose a novel approach that recognizes
\textbf{Con}textual \textbf{So}cial \textbf{R}elationships (\textbf{ConSoR})
from a social cognitive perspective. Specifically, to incorporate social-aware
semantics, we build a lightweight adapter upon the frozen CLIP to learn social
concepts via our novel multi-modal side adapter tuning mechanism. Further, we
construct social-aware descriptive language prompts (e.g., scene, activity,
objects, emotions) with social relationships for each image, and then compel
ConSoR to concentrate more intensively on the decisive visual social factors
via visual-linguistic contrasting. Impressively, ConSoR outperforms previous
methods with a 12.2\% gain on the People-in-Social-Context (PISC) dataset and a
9.8\% increase on the People-in-Photo-Album (PIPA) benchmark. Furthermore, we
observe that ConSoR excels at finding critical visual evidence to reveal social
relationships.
