Despite the recent advances in large-scale video analysis, action detection remains as one
of the most challenging unsolved problems in computer vision. This snag is in part due to the
large volume of data that needs to be analyzed to detect actions in videos. Existing
approaches have mitigated the computational cost, but still, these methods lack rich high-
level semantics that helps them to localize the actions quickly. In this paper, we introduce a
Semantic Cascade Context (SCC) model that aims to detect action in long video sequences …

Despite the recent advances in large-scale video analysis, action detection remains as one
of the most challenging unsolved problems in computer vision. This snag is in part due to the
large volume of data that needs to be analyzed to detect actions in videos. Existing
approaches have mitigated the computational cost, but still, these methods lack rich high-
level semantics that helps them to localize the actions quickly. In this paper, we introduce a
Semantic Cascade Context (SCC) model that aims to detect action in long video sequences …