Achieving realistic, vivid, and human-like synthesized conversational gestures conditioned
on multi-modal data is still an unsolved problem due to the lack of available datasets …

Sign Languages (SL) serve as the primary mode of communication for the Deaf and Hard of
Hearing communities. Deep learning methods for SL recognition and translation have …

In this work, we introduce the BBC-Oxford British Sign Language (BOBSL) dataset, a large-
scale video collection of British Sign Language (BSL). BOBSL is an extended and publicly …

Temporal sign segmentation aims to temporarily divide continuous sign language into
category-agnostic sign segments. One of the challenges to temporal sign segmentation is …

This paper addresses the problem of diversity-aware sign language production, where we
want to give an image (or sequence) of a signer and produce another image with the same …

This paper proposes, analyzes, and evaluates a deep learning architecture based on
transformers for generating sign language motion from sign phonemes (represented using …

Video splicing based sign language synthesis focuses on splicing word\sentence-level sign
language videos to produce new sign language videos. However, directly splicing or …

This paper proposes, analyzes, and evaluates a deep learning architecture based on
transformers for generating sign language motion from sign phonemes (represented using …

This survey paper presents a summary of current work on the Indian Sign Language
Translation in real time. Various approaches to this translation and the use of artificial …

The deaf and dumb community uses sign language to communicate. Sign language is a
language of signs including facial expressions and not of spoken words. It is a visual mode …