Abstract Sign Languages (SLs) are employed by deaf and hard-of-hearing (DHH) people to
communicate on a daily basis. However, the communication with hearing people still faces …

This work presents a meta study covering around 300 published sign language recognition
papers with over 400 experimental results. It includes most papers between the start of the …

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 …

Abstract Prior work on Sign Language Translation has shown that having a mid-level sign
gloss representation (effectively recognizing the individual signs) improves the translation …

This paper proposes a simple transfer learning baseline for sign language translation.
Existing sign language datasets (eg PHOENIX-2014T, CSL-Daily) contain only about 10K …

Developing successful sign language recognition, generation, and translation systems
requires expertise in a wide range of fields, including computer vision, computer graphics …

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 …

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 …