mlsanityData to 7 Oct 2026

A Comprehensive Review of Sign Language Recognition: Different Types, Modalities, and Datasets

arXiv 2204.03328 ↗First posted 7 Apr 2022cs.CV cs.AI cs.CLcited by 5

Not on the map. Why?

Abstract (arXiv)

A machine can understand human activities, and the meaning of signs can help overcome the communication barriers between the inaudible and ordinary people. Sign Language Recognition (SLR) is a fascinating research area and a crucial task concerning computer vision and pattern recognition. Recently, SLR usage has increased in many applications, but the environment, background image resolution, modalities, and datasets affect the performance a lot. Many researchers have been striving to carry out generic real-time SLR models. This review paper facilitates a comprehensive overview of SLR and discusses the needs, challenges, and problems associated with SLR. We study related works about manual and non-manual, various modalities, and datasets. Research progress and existing state-of-the-art SLR models over the past decade have been reviewed. Finally, we find the research gap and limitations in this domain and suggest future directions. This review paper will be helpful for readers and researchers to get complete guidance about SLR and the progressive design of the state-of-the-art SLR model

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 39 of its 156 references that are in the map. First posted on arXiv 7 Apr 2022.

Builds on

39 of 156 references.

References · 39

  1. 2016Stacked Hourglass Networks for Human Pose Estimationcited by 913
  2. 2016Convolutional Pose Machinescited by 325
  3. 2013DeepPose: Human Pose Estimation via Deep Neural Networkscited by 305
  4. 2020Sign Language Transformers: Joint End-to-end Sign Language Recognition and Translationcited by 254
  5. 2017Learning to Estimate 3D Hand Pose from Single RGB Imagescited by 234
  6. 2017GANerated Hands for Real-time 3D Hand Tracking from Monocular RGBcited by 147
  7. 2018MS-ASL: A Large-Scale Data Set and Benchmark for Understanding American Sign Languagecited by 118
  8. 2020BSL-1K: Scaling up co-articulated sign language recognition using mouthing cuescited by 106
  9. 2017V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Mapcited by 102
  10. 2021Skeleton Aware Multi-modal Sign Language Recognitioncited by 101
  11. 2018Cross-modal Deep Variational Hand Pose Estimationcited by 89
  12. 2021Visual Alignment Constraint for Continuous Sign Language Recognitioncited by 79
27 more
  1. 2020AUTSL: A Large Scale Multi-modal Turkish Sign Language Dataset and Baseline Methodscited by 75
  2. 2020TSPNet: Hierarchical Feature Learning via Temporal Semantic Pyramid for Sign Language Translationcited by 75
  3. 2020Spatial-Temporal Multi-Cue Network for Continuous Sign Language Recognitioncited by 74
  4. 2018Neural Sign Language Translation based on Human Keypoint Estimationcited by 65
  5. 2020Transferring Cross-domain Knowledge for Video Sign Language Recognitioncited by 60
  6. 2017BigHand2.2M Benchmark: Hand Pose Dataset and State of the Art Analysiscited by 46
  7. 2020Global-local Enhancement Network for NMFs-aware Sign Language Recognitioncited by 38
  8. 2019Construct Dynamic Graphs for Hand Gesture Recognition via Spatial-Temporal Attentioncited by 22
  9. 2015Hands Deep in Deep Learning for Hand Pose Estimationcited by 20
  10. 2020BosphorusSign22k Sign Language Recognition Datasetcited by 19
  11. 2021Sign Language Recognition via Skeleton-Aware Multi-Model Ensemblecited by 16
  12. 2018Augmented Skeleton Space Transfer for Depth-based Hand Pose Estimationcited by 15
  13. 2017Pose Guided Structured Region Ensemble Network for Cascaded Hand Pose Estimationcited by 12
  14. 2017Towards Good Practices for Deep 3D Hand Pose Estimationcited by 11
  15. 2018DRPose3D: Depth Ranking in 3D Human Pose Estimationcited by 9
  16. 2020Score-level Multi Cue Fusion for Sign Language Recognitioncited by 7
  17. 2016Efficiently Creating 3D Training Data for Fine Hand Pose Estimationcited by 6
  18. 20183D human pose estimation from depth maps using a deep combination of posescited by 6
  19. 2021Context Matters: Self-Attention for Sign Language Recognitioncited by 5
  20. 2013Indian Sign Language Recognition Using Eigen Value Weighted Euclidean Distance Based Classification Techniquecited by 4
  21. 2017Large-scale Isolated Gesture Recognition Using Convolutional Neural Networkscited by 4
  22. 2018HGR-Net: A Fusion Network for Hand Gesture Segmentation and Recognitioncited by 4
  23. 2016Multi-Modality Fusion based on Consensus-Voting and 3D Convolution for Isolated Gesture Recognitioncited by 3
  24. 2017Hand3D: Hand Pose Estimation using 3D Neural Networkcited by 3
  25. 2017End-to-end Global to Local CNN Learning for Hand Pose Recovery in Depth Datacited by 3
  26. 2020American Sign Language Recognition Using RF Sensingcited by 2
  27. 2021Application of Transfer Learning to Sign Language Recognition using an Inflated 3D Deep Convolutional Neural Networkcited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 1; 2025: 1; 2026: 1.

5 papers.

  1. 2023A Survey on Deep Multi-modal Learning for Body Language Recognition and Generationcited by 3
  2. 2024Sign Language Recognition Based On Facial Expression and Hand Skeletoncited by 1
  3. 2023Live American Sign Language Letter Classification with Convolutional Neural Networkscited by 0
  4. 2025Fine-Tuning Video Transformers for Word-Level Bangla Sign Language: A Comparative Analysis for Classification Taskscited by 0
  5. 2026Sign-Language Datasets at Scale: A Comprehensive Survey on Resources, Benchmarks, and Annotation Standardscited by 0