Asl2000 I3d
This is a pre-trained I3D (Inflated 3D ConvNet) model for American Sign Language recognition with 2000 classes.
Source du modèle
- Type
- Other
- Taille du fichier
- 54,9 MB
- Version
- vRevision 80314a7
- Mis à jour
- 4 oct. 2026
- Téléchargements
- 18
- Source
- Hugging Face
Description de la source
ASL2000: American Sign Language Recognition Model
Model Description
This is a pre-trained I3D (Inflated 3D ConvNet) model for American Sign Language recognition with 2000 classes.
- Architecture: I3D (Inflated 3D ConvNet)
- Dataset: WLASL (Word-Level American Sign Language)
- Classes: 2000 ASL words
- Performance:
- Top-1 Accuracy: 32.48%
- Top-5 Accuracy: 57.31%
- Top-10 Accuracy: 66.31%
Usage
import torch
from pytorch_i3d import InceptionI3d
# Load model
model = InceptionI3d(400, in_channels=3)
model.load_state_dict(torch.load('weights/rgb_imagenet.pt', map_location='cpu'))
model.replace_logits(2000)
model.load_state_dict(torch.load('asl2000_model.pt', map_location='cpu'))
model.eval()
# Run inference on video
# See inference.py for complete example
Citation
@inproceedings{li2020word,
title={Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison},
author={Li, Dongxu and Rodriguez, Cristian and Yu, Xin and Li, Hongdong},
booktitle={The IEEE Winter Conference on Applications of Computer Vision},
pages={1459--1469},
year={2020}
}
License
MIT License - Academic use only
Sources
1 source
Sources
1 sourceVérifié 21 août
Artefacts du modèle
1 artefact
Artefacts du modèle
1 artefactExtraits de sources
2 extraits
Extraits de sources
2 extraits--- license: mit tags: - video-classification - sign-language - asl - american-sign-language - i3d - wlasl datasets: - WLASL --- # ASL2000: American Sign Language Recognition Model ## Model Description This is a pre-trained I3D (Inflated 3D ConvNet) model for American Sign Language recognition with 2000 classes. - **Architecture:** I3D (Inflated 3D ConvNet) - **Dataset:** WLASL (Word-Level American Sign Language) - **Classes:** 2000 ASL words - **Performance:** - Top-1 Accuracy: 32.48% - Top-5 Accuracy: 57.31% - Top-10 Accuracy: 66.31% ## Usage ```python import torch from pytorch_i3d import InceptionI3d # Load model model = InceptionI3d(400, in_channels=3) model.load_state_dict(torch.load('weights/rgb_imagenet.pt', map_location='cpu')) model.replace_logits(2000) model.load_state_dict(torch.load('asl2000_model.pt', map_location='cpu')) model.eval() # Run inference on video # See inference.py for complete example ``` ## Citation ``` @inproceedings{li2020word, title={Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison}, author={Li, Dongxu and Rodriguez, Cristian and Yu, Xin and Li, Hongdong}, booktitle={The IEEE Winter Conference on Applications of Computer Vision}, pages={1459--1469}, year={2020} } ``` ## License MIT License - Academic use only
Source context: 18 downloads · 1 likes · Pipeline video-classification · Repo raghuhasan/asl2000-i3d
