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Recognizing actions in videos is rapidly becoming a topic of much research. To facilitate the development of methods for action recognition, several video collections, along with benchmark protocols, have previously been proposed. In this paper, we present a novel video database, the "Action Similarity LAbeliNg" (ASLAN) database, along with benchmark protocols. The ASLAN set includes thousands of videos collected from the web, in over 400 complex action classes. Our benchmark protocols focus ondoi:10.1109/tpami.2011.209 pmid:22262724 fatcat:o4je6q3ilbhrpb6yfrinrsknsi