Robust Keypoint Normalization Method for Korean Sign Language Translation using Transformer
ICTC(2020)
摘要
In this paper, We propose a robust keypoint normalization method for sign language translation framework using Transformer. The proposed method normalizes human keypoints based on the length of the neck-shoulder bone. The normalized keypoints are utilized for the Transformer-based framework as an input sequence. In our extensive experiments, the proposed normalization method greatly improves the accuracy and robustness of sign language translation.
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关键词
sign language translation, Transformer, human keypoint detection
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