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 …

In this work, we show that a late fusion approach to multimodality in sign language
recognition improves the overall ability of the model in comparison to the singular …

Recognizing human gestures in sign language is a complex and challenging task. Human
sign language gestures are a combination of independent hand and finger articulations …

Sign language recognition is considered the most important and challenging application in
gesture recognition, involving the fields of pattern recognition, machine learning and …

Currently, one of the challenging and most interesting human action recognition (HAR)
problems is the 3D sign language recognition problem. The sign in the 3D video can be …

Sign Language is the only method used in communication between the hearing-impaired
community and common community. Sign Language Recognition (SLR) system, which is …

In the sign language alphabet, several hand signs are in use. Automatic recognition of
dynamic hand gestures could facilitate several applications such as people with a speech …

Sign Language recognition systems aid communication among deaf people, hearing
impaired people, and speakers. One of the types of signals that has seen increased studies …

Abstract 3D Sign language recognition is challenging from capturing to recognition. 3D
signs are a set of spatio temporal variations of hands and fingers with respect to face, head …

Recent advances regarding deep generative models have strengthened a realm of
approaches in which discriminative and generative tasks are tackled jointly in an analysis-by …