# BBC-Oxford British Sign Language Dataset

arXiv: https://arxiv.org/abs/2111.03635 · HTML: https://mlsanity.com/paper/2111.03635/

## Key facts

- Cited by 28 papers in the map (data through 14 Oct 2026).
- Builds on 37 of its 69 references that are in the map.
- First posted on arXiv 5 Nov 2021.

## Builds on (most cited first, 30 of 37)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Squeeze-and-Excitation Networks](https://mlsanity.com/paper/1709.01507/) (2017)
- [MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications](https://mlsanity.com/paper/1704.04861/) (2017)
- [Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset](https://mlsanity.com/paper/1705.07750/) (2017)
- [RAFT: Recurrent All-Pairs Field Transforms for Optical Flow](https://mlsanity.com/paper/2003.12039/) (2020)
- [OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields](https://mlsanity.com/paper/1812.08008/) (2018)
- [Two-Stream Convolutional Networks for Action Recognition in Videos](https://mlsanity.com/paper/1406.2199/) (2014)
- [WIDER FACE: A Face Detection Benchmark](https://mlsanity.com/paper/1511.06523/) (2015)
- [Sign Language Transformers: Joint End-to-end Sign Language Recognition and Translation](https://mlsanity.com/paper/2003.13830/) (2020)
- [Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison](https://mlsanity.com/paper/1910.11006/) (2019)
- [Improving Sign Language Translation with Monolingual Data by Sign Back-Translation](https://mlsanity.com/paper/2105.12397/) (2021)
- [How2Sign: A Large-scale Multimodal Dataset for Continuous American Sign Language](https://mlsanity.com/paper/2008.08143/) (2020)
- [The VIA Annotation Software for Images, Audio and Video](https://mlsanity.com/paper/1904.10699/) (2019)
- [RetinaFace: Single-stage Dense Face Localisation in the Wild](https://mlsanity.com/paper/1905.00641/) (2019)
- [MS-ASL: A Large-Scale Data Set and Benchmark for Understanding American Sign Language](https://mlsanity.com/paper/1812.01053/) (2018)
- [BSL-1K: Scaling up co-articulated sign language recognition using mouthing cues](https://mlsanity.com/paper/2007.12131/) (2020)
- [Video-based Sign Language Recognition without Temporal Segmentation](https://mlsanity.com/paper/1801.10111/) (2018)
- [Sign Language Recognition, Generation, and Translation: An Interdisciplinary Perspective](https://mlsanity.com/paper/1908.08597/) (2019)
- [AUTSL: A Large Scale Multi-modal Turkish Sign Language Dataset and Baseline Methods](https://mlsanity.com/paper/2008.00932/) (2020)
- [Including Signed Languages in Natural Language Processing](https://mlsanity.com/paper/2105.05222/) (2021)
- [Neural Sign Language Translation based on Human Keypoint Estimation](https://mlsanity.com/paper/1811.11436/) (2018)
- [Watch, read and lookup: learning to spot signs from multiple supervisors](https://mlsanity.com/paper/2010.04002/) (2020)
- [Read and Attend: Temporal Localisation in Sign Language Videos](https://mlsanity.com/paper/2103.16481/) (2021)
- [Content4All Open Research Sign Language Translation Datasets](https://mlsanity.com/paper/2105.02351/) (2021)
- [Skeletor: Skeletal Transformers for Robust Body-Pose Estimation](https://mlsanity.com/paper/2104.11712/) (2021)
- [Aligning Subtitles in Sign Language Videos](https://mlsanity.com/paper/2105.02877/) (2021)
- [Seeing wake words: Audio-visual Keyword Spotting](https://mlsanity.com/paper/2009.01225/) (2020)
- [BosphorusSign22k Sign Language Recognition Dataset](https://mlsanity.com/paper/2004.01283/) (2020)
- [Zero-shot keyword spotting for visual speech recognition in-the-wild](https://mlsanity.com/paper/1807.08469/) (2018)

## Built on by (most cited first, 28 of 28)

- [Open-Domain Sign Language Translation Learned from Online Video](https://mlsanity.com/paper/2205.12870/) (2022)
- [Sign Language Video Retrieval with Free-Form Textual Queries](https://mlsanity.com/paper/2201.02495/) (2022)
- [Scaling up Multimodal Pre-training for Sign Language Understanding](https://mlsanity.com/paper/2408.08544/) (2024)
- [Automatic dense annotation of large-vocabulary sign language videos](https://mlsanity.com/paper/2208.02802/) (2022)
- [Improving 3D Pose Estimation for Sign Language](https://mlsanity.com/paper/2308.09525/) (2023)
- [Is context all you need? Scaling Neural Sign Language Translation to Large Domains of Discourse](https://mlsanity.com/paper/2308.09622/) (2023)
- [Scaling up sign spotting through sign language dictionaries](https://mlsanity.com/paper/2205.04152/) (2022)
- [Geo-Sign: Hyperbolic Contrastive Regularisation for Geometrically Aware Sign Language Translation](https://mlsanity.com/paper/2506.00129/) (2025)
- [Signing Outside the Studio: Benchmarking Background Robustness for Continuous Sign Language Recognition](https://mlsanity.com/paper/2211.00448/) (2022)
- [A New Dataset for End-to-End Sign Language Translation: The Greek Elementary School Dataset](https://mlsanity.com/paper/2310.04753/) (2023)
- [Deep Understanding of Sign Language for Sign to Subtitle Alignment](https://mlsanity.com/paper/2503.03287/) (2025)
- [Learnt Contrastive Concept Embeddings for Sign Recognition](https://mlsanity.com/paper/2308.09515/) (2023)
- [A Sign Language Recognition System with Pepper, Lightweight-Transformer, and LLM](https://mlsanity.com/paper/2309.16898/) (2023)
- [Gloss Alignment Using Word Embeddings](https://mlsanity.com/paper/2308.04248/) (2023)
- [SignVLA: A Gloss-Free Vision-Language-Action Framework for Real-Time Sign Language-Guided Robotic Manipulation](https://mlsanity.com/paper/2602.22514/) (2026)
- [ISLTranslate: Dataset for Translating Indian Sign Language](https://mlsanity.com/paper/2307.05440/) (2023)
- [SignSparK: Efficient Multilingual Sign Language Production via Sparse Keyframe Learning](https://mlsanity.com/paper/2603.10446/) (2026)
- [ASL-Homework-RGBD Dataset: An annotated dataset of 45 fluent and non-fluent signers performing American Sign Language homeworks](https://mlsanity.com/paper/2207.04021/) (2022)
- [Toward American Sign Language Processing in the Real World: Data, Tasks, and Methods](https://mlsanity.com/paper/2308.12419/) (2023)
- [Diverse Sign Language Translation](https://mlsanity.com/paper/2410.19586/) (2024)
- [Bootstrapping Sign Language Annotations with Sign Language Models](https://mlsanity.com/paper/2604.07606/) (2026)
- [SignDATA: Data Pipeline for Sign Language Translation](https://mlsanity.com/paper/2604.20357/) (2026)
- [SIGNET: Motion-Level Knowledge Transfer for Cross-Language Sign Language Translation](https://mlsanity.com/paper/2606.28626/) (2026)
- [AutoSign: Direct Pose-to-Text Translation for Continuous Sign Language Recognition](https://mlsanity.com/paper/2507.19840/) (2025)
- [iLSU-T: an Open Dataset for Uruguayan Sign Language Translation](https://mlsanity.com/paper/2507.21104/) (2025)
- [Emotion Recognition in Sign Language Conversation](https://mlsanity.com/paper/2605.23328/) (2026)
- [Beyond BLEU: A Case for Redefining Sign Language Translation Benchmarks](https://mlsanity.com/paper/2609.03734/) (2026)
- [ReSCUE: Re-translation with Sentence Commitment for Unsegmented Long-Form Simultaneous Sign Language Translation](https://mlsanity.com/paper/2610.03022/) (2026)

## Abstract (arXiv)

In this work, we introduce the BBC-Oxford British Sign Language (BOBSL) dataset, a large-scale video collection of British Sign Language (BSL). BOBSL is an extended and publicly released dataset based on the BSL-1K dataset introduced in previous work. We describe the motivation for the dataset, together with statistics and available annotations. We conduct experiments to provide baselines for the tasks of sign recognition, sign language alignment, and sign language translation. Finally, we describe several strengths and limitations of the data from the perspectives of machine learning and linguistics, note sources of bias present in the dataset, and discuss potential applications of BOBSL in the context of sign language technology. The dataset is available at https://www.robots.ox.ac.uk/~vgg/data/bobsl/.