Datasets:
metadata
annotations_creators: []
language: en
license: other
size_categories:
- 10K<n<100K
task_categories:
- video-classification
task_ids: []
pretty_name: World Level American Sign Language
tags:
- fiftyone
- video
- activity-recognition
- asl
- sign-language
dataset_summary: >
![image/png](dataset_preview.gif)
This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 11980
samples.
## Installation
If you haven't already, install FiftyOne:
```bash
pip install -U fiftyone
```
## Usage
```python
import fiftyone as fo
import fiftyone.utils.huggingface as fouh
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = fouh.load_from_hub("Voxel51/WLASL")
# Launch the App
session = fo.launch_app(dataset)
```
Dataset Card for WLASL
This is a FiftyOne video dataset with 11980 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
import fiftyone.utils.huggingface as fouh
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = fouh.load_from_hub("Voxel51/WLASL")
# Launch the App
session = fo.launch_app(dataset)
Dataset Details
Dataset Description
WLASL is the largest video dataset for Word-Level American Sign Language (ASL) recognition, which features 2,000 common different words in ASL. The authors hope WLASL will facilitate the research in sign language understanding and eventually benefit the communication between deaf and hearing communities.
- Curated by: Dongxu Li and Hongdong Li
- Language(s) (NLP): en
- License: other
Dataset Sources
- Repository: https://github.com/dxli94/WLASL
- Paper: https://arxiv.org/abs/1910.11006
- Homepage: https://dxli94.github.io/WLASL/
- Demo: https://try.fiftyone.ai/datasets/asl-dataset/samples
Uses
All the WLASL data is intended for academic and computational use only. No commercial usage is allowed. Licensed under the Computational Use of Data Agreement (C-UDA)
Citation
BibTeX:
@misc{li2020wordlevel,
title={Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison},
author={Dongxu Li and Cristian Rodriguez Opazo and Xin Yu and Hongdong Li},
year={2020},
eprint={1910.11006},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
@inproceedings{li2020transferring,
title={Transferring cross-domain knowledge for video sign language recognition},
author={Li, Dongxu and Yu, Xin and Xu, Chenchen and Petersson, Lars and Li, Hongdong},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={6205--6214},
year={2020}
}