Decoupled and Boosted Learning for Skeleton-based Dynamic Hand Gesture Recognition

Introduction

In this paper, we propose a lightweight dual-stream framework based on decoupled and boosted learning for skeleton-based dynamic hand gesture recognition. We evaluate our model on three challenging datasets: SHREC’17 Track dataset, FPHA dataset, and DHG-14/28 dataset. Experimental results show the superiority of our method.

Requirements

• Python 3.8
• Tensorflow 2.4.1
• numpy
• tqdm
• scipy
• opencv

Test Model

• You can directly download the trained models from here.

1. Run the following command to test models.

python test.py