  We propose a bidirectional consecutively connected two-pathway network (BCCN)
for efficient gesture recognition. The BCCN consists of two pathways: (i) a
keyframe pathway and (ii) a temporal-attention pathway. The keyframe pathway is
configured using the skeleton-based keyframe selection module. Keyframes pass
through the pathway to extract the spatial feature of itself, and the
temporal-attention pathway extracts temporal semantics. Our model improved
gesture recognition performance in videos and obtained better activation maps
for spatial and temporal properties. Tests were performed on the Chalearn
dataset, the ETRI-Activity 3D dataset, and the Toyota Smart Home dataset.
