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Matyáš Boháček
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Update the description
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app.py
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@@ -112,8 +112,9 @@ Our efforts on lightweight and efficient models for sign language recognition we
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- **WACV2022** - Original SPOTER paper - [Paper](https://openaccess.thecvf.com/content/WACV2022W/HADCV/papers/Bohacek_Sign_Pose-Based_Transformer_for_Word-Level_Sign_Language_Recognition_WACVW_2022_paper.pdf), [Code](https://github.com/matyasbohacek/spoter)
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- **CVPR2022 (AVA Worshop)** - Follow-up WIP – [Extended Abstract](https://drive.google.com/file/d/1Szbhi7ZwZ6VAWAcGcDDU6qV9Uj9xnDsS/view?usp=sharing), [Poster](https://drive.google.com/file/d/1_xvmTNbLjTrx6psKdsLkufAtfmI5wfbF/view?usp=sharing)
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### How to sign?
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The model wrapped in this demo was trained on [WLASL100](https://dxli94.github.io/WLASL/), so it only knows selected ASL vocabulary. Take a look at these tutorial video examples (this is how you sign [computer](https://www.handspeak.com/word/search/index.php?id=449), [work](https://www.handspeak.com/word/search/index.php?id=2423), or [time](https://www.handspeak.com/word/search/index.php?id=2223)), try to replicate them yourself, and have them recognized using the webcam capture below. Have fun!
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css="""
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@font-face {
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font-family: Graphik;
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- **WACV2022** - Original SPOTER paper - [Paper](https://openaccess.thecvf.com/content/WACV2022W/HADCV/papers/Bohacek_Sign_Pose-Based_Transformer_for_Word-Level_Sign_Language_Recognition_WACVW_2022_paper.pdf), [Code](https://github.com/matyasbohacek/spoter)
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- **CVPR2022 (AVA Worshop)** - Follow-up WIP – [Extended Abstract](https://drive.google.com/file/d/1Szbhi7ZwZ6VAWAcGcDDU6qV9Uj9xnDsS/view?usp=sharing), [Poster](https://drive.google.com/file/d/1_xvmTNbLjTrx6psKdsLkufAtfmI5wfbF/view?usp=sharing)
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### How to sign?
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The model wrapped in this demo was trained on [WLASL100](https://dxli94.github.io/WLASL/), so it only knows selected ASL vocabulary. Take a look at these tutorial video examples (this is how you sign [computer](https://www.handspeak.com/word/search/index.php?id=449), [work](https://www.handspeak.com/word/search/index.php?id=2423), or [time](https://www.handspeak.com/word/search/index.php?id=2223)), try to replicate them yourself, and have them recognized using the webcam capture below. Have fun!
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> The demo can analyze webcam recordings or your uploaded videos. Before you hit Submit, **don't forget to select the input source in the dropdown first**.""",
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article="This is joint work of [Matyas Bohacek](https://scholar.google.cz/citations?user=wDy1xBwAAAAJ) and [Zhuo Cao](https://www.linkedin.com/in/zhuo-cao-b0787a1aa/?originalSubdomain=hk). For more info, visit [our website](https://www.signlanguagerecognition.com). To contact us, drop an e-mail [here](mailto:[email protected]).",
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css="""
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@font-face {
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font-family: Graphik;
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