AI technologies for Natural Languages have made tremendous progress recently. However,
commensurate progress has not been made on Sign Languages, in particular, in …

Sign Language Recognition (SLR) targets on interpreting the sign language into text or
speech, so as to facilitate the communication between deaf-mute people and ordinary …

In recent years, Word-level Sign Language Recognition (WSLR) research has gained
popularity in the computer vision community, and thus various approaches have been …

In this paper we present a system for word-level sign language recognition based on the
Transformer model. We aim at a solution with low computational cost, since we see great …

Despite the recent success of deep learning in video-related tasks, deep models typically
focus on the most discriminative features, ignoring other potentially non-trivial and …

Continuous sign language recognition (SLR) aims to translate a signing sequence into a
sentence. It is very challenging as sign language is rich in vocabulary, while many among …

Sign languages are visual languages using manual articulations and non-manual elements
to convey information. For sign language recognition and translation, the majority of existing …

Accumulative representations provide a method for representing variable-length videos with
constant length features. In this study, we present aligned temporal accumulative features …

Sign Language Recognition (SLR) represents a revolutionary technology aiming to
establish communication between hearing impaired and non-hearing impaired …

Sign language is the primary way of communication between deaf people, but the majority of
hearing people do not know how to sign. The reliance of deaf people on interpreters is both …