ISLR

SignBERT+: Hand-model-aware Self-supervised Pre-training for Sign Language Understanding
Hand gesture serves as a crucial role during the expression of sign language. Current deep learning based methods for sign language …
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BEST: BERT Pre-Training for Sign Language Recognition with Coupling Tokenization
In this work, we are dedicated to leveraging the BERT pre-training success and modeling the domain-specific statistics to fertilize the …
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SignBERT: Pre-Training of Hand-Model-Aware Representation for Sign Language Recognition
Hand gesture serves as a critical role in sign language. Current deep-learning-based sign language recognition (SLR) methods may suffer …
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Global-Local Enhancement Network for NMF-Aware Sign Language Recognition
Sign language recognition (SLR) is a challenging problem, involving complex manual features (i.e., hand gestures) and fine-grained …
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Hand-Model-Aware Sign Language Recognition
Hand gestures play a dominant role in the expression of sign language. Current deep-learning based video sign language recognition …
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Video-based sign language recognition without temporal segmentation
Millions of hearing impaired people around the world routinely use some variants of sign languages to communicate, thus the automatic …
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Attention-Based 3D-CNNs for Large-Vocabulary Sign Language Recognition
Sign language recognition (SLR) is an important and challenging research topic in the multimedia field. Conventional techniques for SLR …
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Sign Language Recognition with Multi-modal Features
We study the problem of recognizing sign language automatically using the RGB videos and skeleton coordinates captured by Kinect, which …
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Sign language recognition based on adaptive HMMs with data augmentation
Vision based sign language recognition (SLR) is a challenging task due to the complexity of signs and limited data collection. To …
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Sign language recognition with long short-term memory
Sign Language Recognition (SLR) aims at translating the Sign Language (SL) into speech or text, so as to facilitate the communication …
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