# BosphorusSign22k Sign Language Recognition Dataset

arXiv: https://arxiv.org/abs/2004.01283 · HTML: https://mlsanity.com/paper/2004.01283/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Apr 2020.

## Built on by (most cited first, 19 of 19)

- [BBC-Oxford British Sign Language Dataset](https://mlsanity.com/paper/2111.03635/) (2021)
- [Using Motion History Images with 3D Convolutional Networks in Isolated Sign Language Recognition](https://mlsanity.com/paper/2110.12396/) (2021)
- [Survey on Hand Gesture Recognition from Visual Input](https://mlsanity.com/paper/2501.11992/) (2025)
- [A New Dataset for End-to-End Sign Language Translation: The Greek Elementary School Dataset](https://mlsanity.com/paper/2310.04753/) (2023)
- [A Hong Kong Sign Language Corpus Collected from Sign-interpreted TV News](https://mlsanity.com/paper/2405.00980/) (2024)
- [Hierarchical Windowed Graph Attention Network and a Large Scale Dataset for Isolated Indian Sign Language Recognition](https://mlsanity.com/paper/2407.14224/) (2024)
- [MM-WLAuslan: Multi-View Multi-Modal Word-Level Australian Sign Language Recognition Dataset](https://mlsanity.com/paper/2410.19488/) (2024)
- [A Comprehensive Review of Sign Language Recognition: Different Types, Modalities, and Datasets](https://mlsanity.com/paper/2204.03328/) (2022)
- [Transfer Learning for Cross-dataset Isolated Sign Language Recognition in Under-Resourced Datasets](https://mlsanity.com/paper/2403.14534/) (2024)
- [A Chinese Continuous Sign Language Dataset Based on Complex Environments](https://mlsanity.com/paper/2409.11960/) (2024)
- [Logos as a Well-Tempered Pre-train for Sign Language Recognition](https://mlsanity.com/paper/2505.10481/) (2025)
- [E-TSL: A Continuous Educational Turkish Sign Language Dataset with Baseline Methods](https://mlsanity.com/paper/2405.02984/) (2024)
- [AzSLD: Azerbaijani Sign Language Dataset for Fingerspelling, Word, and Sentence Translation with Baseline Software](https://mlsanity.com/paper/2411.12865/) (2024)
- [SignAgent: Agentic LLMs for Linguistically-Grounded Sign Language Annotation and Dataset Curation](https://mlsanity.com/paper/2603.19059/) (2026)
- [SkelCap: Automated Generation of Descriptive Text from Skeleton Keypoint Sequences](https://mlsanity.com/paper/2405.02977/) (2024)
- [RoCoISLR: A Romanian Corpus for Isolated Sign Language Recognition](https://mlsanity.com/paper/2511.12767/) (2025)
- [Sign-Language Datasets at Scale: A Comprehensive Survey on Resources, Benchmarks, and Annotation Standards](https://mlsanity.com/paper/2606.19352/) (2026)
- [JSL-DC: A Word-Level Japanese Sign Language Dataset with Linguist-Derived Descriptions for Distinguishing Confusable Signs](https://mlsanity.com/paper/2608.18412/) (2026)
- [Machine Translation for Sign Languages](https://mlsanity.com/paper/2610.00881/) (2026)

## Abstract (arXiv)

Sign Language Recognition is a challenging research domain. It has recently seen several advancements with the increased availability of data. In this paper, we introduce the BosphorusSign22k, a publicly available large scale sign language dataset aimed at computer vision, video recognition and deep learning research communities. The primary objective of this dataset is to serve as a new benchmark in Turkish Sign Language Recognition for its vast lexicon, the high number of repetitions by native signers, high recording quality, and the unique syntactic properties of the signs it encompasses. We also provide state-of-the-art human pose estimates to encourage other tasks such as Sign Language Production. We survey other publicly available datasets and expand on how BosphorusSign22k can contribute to future research that is being made possible through the widespread availability of similar Sign Language resources. We have conducted extensive experiments and present baseline results to underpin future research on our dataset.