Masked Batch Normalization to Improve Tracking-Based Sign Language Recognition Using Graph Convolutional Networks

Sign language recognition is a fundamental technique to improve communication between native signers and speakers. Current state-of-the-art sign language recognition methods often apply deep neural network models to learn an optimized projection between sign language videos and sentences in an end-to-end manner. Generally, minibatch training using sequential data requires the addition of padding t...