Enhanced dynamic sign language recognition using slowfast networks

no code implementations • IEEE 2021 • Ahmed Hassan, Ahmed Elgabry, Elsayed Hemayed

Through this transfer learning approach, we introduced a new state-of-the-art accuracy on the WLASL300 (300 words e. g., 300 classes) dataset with an improvement of 23. 2 % top-1 accuracy compared to the previous state-of-the-art introduced in the WLASL paper using an I3D model.

Sign Language Recognition Transfer Learning