Paper Title
Multi-View Isolated Sign Language Recognition Based on Feature Generated Network

Abstract
Multi-view data is widely recognized as being particularly advantageous for sign language recognition, as it can help to avoid recognition errors caused by observation angles, gesture occlusion, and other factors. However, obtaining multi-view data can be very expensive in practice. To address this issue, we propose a novel network that generates multiview features from single-view data for isolated sign language. The experimental results from several multi-view datasets indicate that our model's recognition accuracy with single-view data is comparable to that of models with multi-view data. Keywords - Sign Language Recognition, Generating Feature, Multi-view Data