Separable Spatial-Temporal Convolution Network for Skeleton Aware Multi-modal Sign Language Recognition
Author: Bin Sun
Email: [email protected]
This code is for CVPR 2021 SLR Challenge. Using features from whole-pose HRNet for recognition. Please Cite the Paper
Skeleton Aware Multi-modal Sign Language Recognition https://paperswithcode.com/paper/skeleton-based-sign-language-recognition
@article{jiang2021skeleton,
title={Skeleton Aware Multi-modal Sign Language Recognition},
author={Jiang, Songyao and Sun, Bin and Wang, Lichen and Bai, Yue and Li, Kunpeng and Fu, Yun},
journal={arXiv preprint arXiv:2103.08833},
year={2021}
}
install conda environment using environment.yaml , CUDA version 10.1, pretrained model is saved in:https://drive.google.com/drive/u/0/folders/1eDcLSABi736ilpwK1cNOrLUClHuClQVz
Training:
Follow and run main_process.sh
Testing: download test data unzip the data under ./data
python test.py
The output test_feature_w_val_finetune.pkl is what you need for ensemble process
To get ensemble code, please follow this repo: https://github.com/jackyjsy/CVPR21Chal-SLR