Transfer Learning for Cross-dataset Isolated Sign Language Recognition in Under-Resourced Datasets

arXiv:2403.14534v1 Announce Type: new
Abstract: Sign language recognition (SLR) has recently achieved a breakthrough in performance thanks to deep neural networks trained on large annotated sign datasets. Of the many different sign languages, these annotated datasets are only available for a select few. Since acquiring gloss-level labels on sign language videos is difficult, learning by transferring knowledge from existing annotated sources is useful for recognition in under-resourced sign languages. This study provides a publicly available cross-dataset transfer learning benchmark from …

abstract arxiv cs.cv dataset datasets labels language languages networks neural networks performance recognition transfer transfer learning type