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 …

Sign language recognition (SLR) is a weakly supervised task that annotates sign videos as
textual glosses. Recent studies show that insufficient training caused by the lack of large …

Despite existing pioneering works on sign language translation (SLT), there is a non-trivial
obstacle, ie, the limited quantity of parallel sign-text data. To tackle this parallel data …

This work dedicates to continuous sign language recognition (CSLR), which is a weakly
supervised task dealing with the recognition of continuous signs from videos, without any …

The backbone of most deep-learning-based continuous sign language recognition (CSLR)
models consists of a visual module, a sequential module, and an alignment module …

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 …

Abstract Vision-based Continuous Sign Language Recognition (CSLR) aims to recognize
unsegmented signs from image streams. Overfitting is one of the most critical problems in …

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 …

In recent years, deep learning moves video-based Continuous Sign Language Recognition
(CSLR) significantly forward. Currently, a typical network combination for CSLR includes a …

Sign language is a form of visual communication employing hand gestures, body
movements, and facial expressions. The growing prevalence of hearing impairment has …