Research on continuous sign language recognition (CSLR) is essential to bridge the
communication gap between deaf and hearing individuals. Numerous previous studies have …

Analyzing dance moves and routines is a foundational step in learning dance. Videos are
often utilized at this step, and advancements in machine learning, particularly in human …

This demo paper presents sign. mt, an open-source application pioneering real-time
multilingual bi-directional translation between spoken and signed languages. Harnessing …

Sign Language Production (SLP) is a challenging task, given the limited resources available
and the inherent diversity within sign data. As a result, previous works have suffered from the …

Sign Language Processing (SLP) is an interdisciplinary field comprised of Natural
Language Processing (NLP) and Computer Vision. It is focused on the computational …

We introduce a method for transferring the signer's appearance in sign language skeletal
poses while preserving the sign content. Using estimated poses, we transfer the appearance …

This paper introduces an open-source interface for American Sign Language fingerspell
recognition and semantic pose retrieval, aimed to serve as a stepping stone towards more …

Abstract The Swedish Sign Language (STS) Corpus mainly contains segmentations on the
lexical level (ie signs), which makes it difficult to extract information at clause-or utterance …

In this work, we introduce SwissSLi, the first sign language corpus that contains parallel data
of all three Swiss sign languages, namely Swiss German Sign Language (DSGS), French …

Pose estimation keypoints are widely used in sign language recognition (SLR) as a means
of generalising to unseen signers. Despite the advantages of keypoints, SLR models …