RPAN: An End-to-End Recurrent Pose-Attention Network for Action Recognition in Videos

Recent studies demonstrate the effectiveness of Recurrent Neural Networks (RNNs) for action recognition in videos. However, previous works mainly utilize video-level category as supervision to train RNNs, which may prohibit RNNs to learn complex motion structures along time... (read more)

PDF 2017 IEEE International Conference on Computer Vision (ICCV) 2017 PDF 2017 IEEE International Conference on Computer Vision (ICCV) 2017 Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK BENCHMARK
Skeleton Based Action Recognition J-HMDB RPAN Accuracy (RGB+pose) 83.9 # 5

Methods used in the Paper


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