A multi-branch ResNet architecture with HRNet pose estimation and channel-attention fusion reaches 94.52% Rank-1 gait recognition accuracy on CASIA-B normal walking and leads skeleton-based methods on coat-wearing cases.
Optimal boxes: boosting end-to- end scene text recognition by adjusting annotated bound- ing boxes via reinforcement learning
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Gait Recognition via Deep Residual Networks and Multi-Branch Feature Fusion
A multi-branch ResNet architecture with HRNet pose estimation and channel-attention fusion reaches 94.52% Rank-1 gait recognition accuracy on CASIA-B normal walking and leads skeleton-based methods on coat-wearing cases.