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In this paper, we study the problem of social relational inference using visual concepts which serve as indicators of actors' social interactions. While social network analysis from videos has started to gain attention in the recent years, the existing work either uses proximity or co-occurrence statistics, or exploit a holistic model of the scene content where the relations are assumed to stay constant throughout the video. This work permits changing relations and argues that there exists adoi:10.1109/iccv.2011.6126306 dblp:conf/iccv/DingY11 fatcat:wx2iykymcjc7jopvqxprx3hpuy