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 …

This work presents a statistical recognition approach performing large vocabulary
continuous sign language recognition across different signers. Automatic sign language …

This work presents a new approach to learning a frame-based classifier on weakly labelled
sequence data by embedding a CNN within an iterative EM algorithm. This allows the CNN …

In this work we present a new approach to the field of weakly supervised learning in the
video domain. Our method is relevant to sequence learning problems which can be split up …

Recently, sign language researchers have turned to sign language interpreted TV
broadcasts, comprising (i) a video of continuous signing and (ii) subtitles corresponding to …

Image identification is becoming a crucial step in most of the modern world problem-solving
systems. Approaches for image detection, analysis and classification are available in glut …

This paper tackles the problem of zero-shot sign language recognition (ZSSLR), where the
goal is to leverage models learned over the seen sign classes to recognize the instances of …

This paper deals with robust modelling of mouth shapes in the context of sign language
recognition using deep convolutional neural networks. Sign language mouth shapes are …

Abstract Systems that can efficiently search collections of sign language videos have been
highlighted as a useful application of sign language technology. However, the problem of …

The objective of this paper is to recognize gestures in videos–both localizing the gesture
and classifying it into one of multiple classes. We show that the performance of a gesture …