Asl2000 I3d

--- 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

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