Human body trajectories are a salient cue to identify actions in video. Such body trajectories
are mainly conveyed by hands and face across consecutive frames in 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 and face play an important role in expressing sign language. Their features are
usually especially leveraged to improve system performance. However, to effectively extract …

Sign language is the main communication way for deaf and hard-of-hearing (ie, DHH)
people, which is unfamiliar to most non-deaf and hard-of-hearing (non-DHH) people. To …

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 …

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 …

Sign languages are used as a primary language by approximately 70 million D/deaf people
world-wide. However, most communication technologies operate in spoken and written …

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 …

Word-level sign language recognition (SLR) is a significant task which transcribes a sign
language video into a word. Currently, deep-learning-based frameworks mostly combine …