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1
Multi-Scale Local-Temporal Similarity Fusion for Continuous Sign Language Recognition ...
Abstract: Continuous sign language recognition (cSLR) is a public significant task that transcribes a sign language video into an ordered gloss sequence. It is important to capture the fine-grained gloss-level details, since there is no explicit alignment between sign video frames and the corresponding glosses. Among the past works, one promising way is to adopt a one-dimensional convolutional network (1D-CNN) to temporally fuse the sequential frames. However, CNNs are agnostic to similarity or dissimilarity, and thus are unable to capture local consistent semantics within temporally neighboring frames. To address the issue, we propose to adaptively fuse local features via temporal similarity for this task. Specifically, we devise a Multi-scale Local-Temporal Similarity Fusion Network (mLTSF-Net) as follows: 1) In terms of a specific video frame, we firstly select its similar neighbours with multi-scale receptive regions to accommodate different lengths of glosses. 2) To ensure temporal consistency, we then use ...
Keyword: Computer Vision and Pattern Recognition cs.CV; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.2107.12762
https://arxiv.org/abs/2107.12762
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2
Polyphone Disambiguition in Mandarin Chinese with Semi-Supervised Learning ...
Shi, Yi; Wang, Congyi; Chen, Yu. - : arXiv, 2021
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3
SBERT-WK: A Sentence Embedding Method by Dissecting BERT-based Word Models ...
Wang, Bin; Kuo, C. -C. Jay. - : arXiv, 2020
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4
Modeling Homophone Noise for Robust Neural Machine Translation ...
Qin, Wenjie; Li, Xiang; Sun, Yuhui. - : arXiv, 2020
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