A machine can understand human activities, and the meaning of signs can help overcome
the communication barriers between the inaudible and ordinary people. Sign Language …

Hand gesture serves as a crucial role during the expression of sign language. Current deep
learning based methods for sign language understanding (SLU) are prone to over-fitting due …

Sign languages are visual languages which convey information by signers' handshape,
facial expression, body movement, and so forth. Due to the inherent restriction of …

Hand gesture serves as a critical role in sign language. Current deep-learning-based sign
language recognition (SLR) methods may suffer insufficient interpretability and overfitting …

Recently, sign language researchers have turned to sign language interpreted TV
broadcasts, comprising (i) a video of continuous signing and (ii) subtitles corresponding to …

In this work, we are dedicated to leveraging the BERT pre-training success and modeling
the domain-specific statistics to fertilize the sign language recognition~(SLR) model …

Pose-based approaches for sign language recognition provide light-weight and fast models
that can be adopted in real-time applications. This article presents a framework for isolated …

Hand gestures play a dominant role in the expression of sign language. Current deep-
learning based video sign language recognition (SLR) methods usually follow a data-driven …

Sign language recognition using computational models is a challenging problem that
requires simultaneous spatio-temporal modeling of the multiple sources, ie faces, hands …

Sign language is commonly used by deaf or mute people to communicate but requires
extensive effort to master. It is usually performed with the fast yet delicate movement of hand …