mlsanityData to 7 Oct 2026

Sign Language Production: A Review

arXiv 2103.15910 ↗First posted 29 Mar 2021cs.CVcited by 26

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Abstract (arXiv)

Sign Language is the dominant yet non-primary form of communication language used in the deaf and hearing-impaired community. To make an easy and mutual communication between the hearing-impaired and the hearing communities, building a robust system capable of translating the spoken language into sign language and vice versa is fundamental. To this end, sign language recognition and production are two necessary parts for making such a two-way system. Sign language recognition and production need to cope with some critical challenges. In this survey, we review recent advances in Sign Language Production (SLP) and related areas using deep learning. This survey aims to briefly summarize recent achievements in SLP, discussing their advantages, limitations, and future directions of research.

Key facts. Cited by 26 papers in the map (data through 7 Oct 2026). Builds on 23 of its 89 references that are in the map. First posted on arXiv 29 Mar 2021.

Builds on

23 of 89 references.

References · 23

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11 more
  1. 2017Deformable GANs for Pose-based Human Image Generationcited by 166
  2. 2020Progressive Transformers for End-to-End Sign Language Productioncited by 119
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  4. 2020Multi-channel Transformers for Multi-articulatory Sign Language Translationcited by 71
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  6. 2018Neural Sign Language Translation based on Human Keypoint Estimationcited by 65
  7. 2020Adversarial Training for Multi-Channel Sign Language Productioncited by 57
  8. 2020Everybody Sign Now: Translating Spoken Language to Photo Realistic Sign Language Videocited by 34
  9. 2020Real-Time Sign Language Detection using Human Pose Estimationcited by 28
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 7; 2023: 2; 2024: 10; 2025: 2; 2026: 3.

26 papers.

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  1. 2023One-Stage 3D Whole-Body Mesh Recovery with Component Aware Transformercited by 128
  2. 2024SignCLIP: Connecting Text and Sign Language by Contrastive Learningcited by 20
  3. 2024A Simple Baseline for Spoken Language to Sign Language Translation with 3D Avatarscited by 18
  4. 2024SignAvatar: Sign Language 3D Motion Reconstruction and Generationcited by 14
  5. 2022All You Need In Sign Language Productioncited by 8
  6. 2024Sign Stitching: A Novel Approach to Sign Language Productioncited by 8
  7. 2022TriHorn-Net: A Model for Accurate Depth-Based 3D Hand Pose Estimationcited by 7
  8. 2021ZS-SLR: Zero-Shot Sign Language Recognition from RGB-D Videoscited by 4
  9. 2021Multi-Modal Zero-Shot Sign Language Recognitioncited by 3
  10. 2022Deep-Disaster: Unsupervised Disaster Detection and Localization Using Visual Datacited by 3
  11. 2022Word separation in continuous sign language using isolated signs and post-processingcited by 3
  12. 2023A Survey on Deep Multi-modal Learning for Body Language Recognition and Generationcited by 3
14 more
  1. 2024Select and Reorder: A Novel Approach for Neural Sign Language Productioncited by 3
  2. 20243D-LEX v1.0: 3D Lexicons for American Sign Language and Sign Language of the Netherlandscited by 3
  3. 2022Neural Sign Reenactor: Deep Photorealistic Sign Language Retargetingcited by 2
  4. 2024The NGT200 Dataset: Geometric Multi-View Isolated Sign Recognitioncited by 2
  5. 2022A Non-Anatomical Graph Structure for isolated hand gesture separation in continuous gesture sequencescited by 1
  6. 2024A Transformer Model for Boundary Detection in Continuous Sign Languagecited by 1
  7. 2024Diversity-Aware Sign Language Production through a Pose Encoding Variational Autoencodercited by 1
  8. 2025Flick: Few Labels Text Classification using K-Aware Intermediate Learning in Multi-Task Low-Resource Languagescited by 1
  9. 2022SignNet: Single Channel Sign Generation using Metric Embedded Learningcited by 0
  10. 2024Fusion Embedding for Pose-Guided Person Image Synthesis with Diffusion Modelcited by 0
  11. 2025Towards Skeletal and Signer Noise Reduction in Sign Language Production via Quaternion-Based Pose Encoding and Contrastive Learningcited by 0
  12. 2026Semantic Hardness Is Not Visual Hardness: Sign-Aware Hard Negative Mining for Sign Language Retrievalcited by 0
  13. 2026Bridging the Gap Between Semantics and Reconstruction:Unifying Sign Language Translation and Productioncited by 0
  14. 2026Machine Translation for Sign Languagescited by 0