VSL400: A Multi-view Dataset for Vietnamese Word-Level Sign Language Recognition

2026 · doi:10.22541/au.177075292.21810740/v1
preprint OA: closed
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The paper introduces VSL400, a multi-view, manually annotated video dataset for isolated word-level recognition of Vietnamese Sign Language, containing 74,259 clips covering 400 glosses recorded by 28 signers. Each sign instance is captured simultaneously from three synchronized RGB camera views (front, left, and right), and the authors provide a preprocessing pipeline for boundary detection, temporal segmentation, and spatial normalization with structured metadata. All data, annotations, and baseline processing code are publicly available under an open license, with the stated aim of addressing a low-resource dataset gap for VSL recognition. The authors also note that the work is a preprint and not peer reviewed. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

This research introduces VSL400, a multi-view video dataset created for the isolated wordlevel recognition of Vietnamese Sign Language (VSL). The dataset comprises 74,259 manually annotated video clips, encompassing 400 glosses, and was performed by 28 signers, including both deaf native users and trained hearing signers. Each sign instance was recorded concurrently from three synchronized RGB camera views (front, left, and right), thereby capturing the inherently three-dimensional character of sign articulation. To facilitate reproducible research, we provide a comprehensive preprocessing pipeline for boundary detection, temporal segmentation, and spatial normalization, along with structured metadata. All video data, annotations, and baseline processing code are publicly accessible under an open license. VSL400 addresses a significant resource deficiency for Vietnamese Sign Language and offers a practical reference dataset for the development and evaluation of robust recognition methods in low-resource environments.
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Abstract

This research introduces VSL400, a multi-view video dataset created for the isolated wordlevel recognition of Vietnamese Sign Language (VSL). The dataset comprises 74,259 manually annotated video clips, encompassing 400 glosses, and was performed by 28 signers, including both deaf native users and trained hearing signers. Each sign instance was recorded concurrently from three synchronized RGB camera views (front, left, and right), thereby capturing the inherently three-dimensional character of sign articulation. To facilitate reproducible research, we provide a comprehensive preprocessing pipeline for boundary detection, temporal segmentation, and spatial normalization, along with structured metadata. All video data, annotations, and baseline processing code are publicly accessible under an open license. VSL400 addresses a significant resource deficiency for Vietnamese Sign Language and offers a practical reference dataset for the development and evaluation of robust recognition methods in low-resource environments. Supplementary Material File (vsl400_dataset.pdf) - Download - 4.89 MB Information & Authors Information Version history Copyright This work is licensed under a Creative Commons Attribution 4.0 International License

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Authors Metrics & Citations Metrics Article Usage 474views 114downloads Citations Download citation Trung Nguyen Quoc, Khoi Pham Dang, Viet Truong Duy, et al. VSL400: A Multi-view Dataset for Vietnamese Word-Level Sign Language Recognition. Authorea. 10 February 2026. DOI: https://doi.org/10.22541/au.177075292.21810740/v1 DOI: https://doi.org/10.22541/au.177075292.21810740/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu.

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