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Deep Progressive Reinforcement Learning for Skeleton-Based Action Recognition
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
In this paper, we propose a deep progressive reinforcement learning (DPRL) method for action recognition in skeleton-based videos, which aims to distil the most informative frames and discard ambiguous frames in sequences for recognizing actions. Since the choices of selecting representative frames are multitudinous for each video, we model the frame selection as a progressive process through deep reinforcement learning, during which we progressively adjust the chosen frames by taking two
doi:10.1109/cvpr.2018.00558
dblp:conf/cvpr/TangTLL018
fatcat:gv6x3vml7fe3peiabn5qxa763y