Iterative Alignment Network for Continuous Sign Language Recognition

CVPR 2019 Junfu Pu Wengang Zhou Houqiang Li

In this paper, we propose an alignment network with iterative optimization for weakly supervised continuous sign language recognition. Our framework consists of two modules: a 3D convolutional residual network (3D-ResNet) for feature learning and an encoder-decoder network with connectionist temporal classification (CTC) for sequence modelling... (read more)

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