A large-scale combinatorial benchmark for sign language recognition

Liqing Gao, Liang Wang, Lianyu Hu, Ruize Han, Zekang Liu, Peng Shi, Fanhua Shang, Wei Feng

Abstract: Highlights•The lack of large-scale sign language datasets severely limits the development of SLR.•We propose a novel TEDA strategy to construct a cost-controllable large-scale (CCLS) sign language dataset.•We propose an end-to-end combinatorial SLR framework that allows existing SLR models to be trained on large-scale combinatorial data.