AI technologies can play an important role in breaking down the communication barriers of
deaf or hearing-impaired people with other communities, contributing significantly to their …

Sign language translation (SLT) is a challenging weakly supervised task without word-level
annotations. An effective method of SLT is to leverage multimodal complementarity and to …

Abstract Sign Language Recognition (SLR) targets on interpreting sign language video into
natural language, which largely facilitates mutual communication between the deaf and …

Body language (BL) refers to the non-verbal communication expressed through physical
movements, gestures, facial expressions, and postures. It is a form of communication that …

The research on video isolated sign language recognition (SLR) algorithms has made
leaping progress, but there are problems that need to be solved urgently in the field of SLR …

Temporal action segmentation (TAS) aims to classify and locate actions in the long
untrimmed action sequence. With the success of deep learning, many deep models for …

Abstract Traditional Sign Language Recognition (SLR) suffers from the scale limitation of SL
datasets, which may lead to over-fitting in narrow context and application. In this paper, to …

Sign language recognition (SLR) is a challenging task, which requires a thorough
understanding of spatial-temporal visual features for translating it into comprehensible …

Continuous Chinese sign language recognition (CCSLR) methods have shown their strong
ability to learn excellent model architectures from datasets. However, due to data …

Abstract Continuous Sign Language Recognition (CSLR) is a task which converts a sign
language video into a gloss sequence. The existing deep learning based sign language …