This repository is all you need for Sign Language Study!
📌 This project is licensed under the Apache License 2.0 – see the LICENSE file for details.
- Please refer to this page for more information.
| Dataset | Year | Language | #Samples | #Signers | Domain |
|---|---|---|---|---|---|
| ChicagoFSWild | 2018 | American | 7304 sequences | 168 | Letters + Char |
| ChicagoFSWild+ | 2019 | American | 55,232 sequences | 260 | Letters + Char |
| ArASL | 2019 | Arabic | 54,049 images | 40 | Letters |
| RWTH-FingerSpelling | 2006 | German | 1,400 image sequences | 20 | Letters + Umlauts + Number |
| Dataset | Year | Language | #Samples | #Signers | Domain |
|---|---|---|---|---|---|
| Purdue RVL-SLLL | 2002 | American | 2,576 video clips | 14 | Motion primitives + Handshapes + General |
| Boston ASLLVD | 2008 | American | 9,800 tokens | 6 | General |
| MS-ASL | 2018 | American | 25,513 videos | 222 | General |
| WLASL | 2019 | American | 21,083 videos | 119 | General |
| ASL-100-RGBD | 2020 | American | ~4,150 tokens | 22 | General |
| ASL Citizen | 2023 | American | 83,399 videos | 52 | General |
| LSA-64 | 2016 | Argentina | 3,200 video sequences | 10 | Dictionary |
| Dataset | Year | Language | #Samples | #Signers | Domain |
|---|---|---|---|---|---|
| RWTH-Boston-104 | 2007 | American | 201 sentences | 3 | General |
| How2Sign | 2020 | American | >35k sentences | 11 | General |
| OpenASL | 2022 | American | - | ~220 | General |
| YouTube-ASL | 2023 | American | - | >2500 | General |
| DailyMoth-70h | 2024 | American | 48,386 clips | 1 | News |
| BOBSL | 2021 | British | 1.2M sequences | 39 | General |
| CSL-Daily | 2021 | Chinese | 20,645 videos | 10 | General |
| RWTH-PHOENIX 2012 | 2012 | Germany | 1,980 sentences | 7 | Weather |
| RWTH-PHOENIX 2014 | 2014 | Germany | 6,861 sentences | 9 | Weather |
| RWTH-PHOENIX14T | 2020 | Germany | 8,257 sentences | 9 | Weather |
- [LREC 2022] Challenges with sign language datasets for sign language recognition and translation. Paper
- [Information Processing & Management] Reviewing 25 years of continuous sign language recognition research: Advances, challenges, and prospects. Paper
- [IEEE Access] Sign Language Recognition: A Comprehensive Review of Traditional and Deep Learning Approaches, Datasets, and Challenges. Paper
- [Advanced Robotics] A Review of Deep Learning-Based Approaches to Sign Language Processing. Paper
- [ICCV] Unraveling a Decade: A Comprehensive Survey on Isolated Sign Language Recognition. Paper
- [ICCMC] A Extensive Survey on Sign Language Recognition Methods. Paper
- [ACM TALLIP] State of the Art of Automation in Sign Language: A Systematic Review. Paper
- [Arxiv] A Comprehensive Review of Sign Language Recognition: Different Types, Modalities, and Datasets. Paper
- [Meas. Sens.] Survey on sign language recognition in context of vision-based and deep learning. Paper
- [Open Comput. Sci.] Sign language identification and recognition: A comparative study. Paper
- [IEEE Access] Technological Solutions for Sign Language Recognition: A Scoping Review of Research Trends, Challenges, and Opportunities. Paper
- [ICITIIT] ML Based Sign Language Recognition System. Paper
- [ScienceDirect] Sign Language Recognition: A Deep Survey. Paper
- [Sensors] Artificial Intelligence Technologies for Sign Language. Paper
- [IEEE Access] Deep Learning for Sign Language Recognition: Current Techniques, Benchmarks, and Open Issues. Paper
- [ISA] Machine Learning Methods for Sign Language Recognition: A Critical Review and Analysis. Paper
- [INOCON] Sign Language Recognition Techniques- A Review. Paper
- [Arab. J. Sci. Eng.] A Survey on Artificial Intelligence in Chinese Sign Language Recognition. Paper
- [J. Eng. Appl. Sci.] Advances, challenges and opportunities in continuous sign language recognition. Paper
- [MTA] Understanding Vision-Based Continuous Sign Language Recognition. Paper
- [EAAI] A Comprehensive Survey and Taxonomy of Sign Language Research. Paper
- [Arxiv] Quantitative Survey of the State of the Art in Sign Language Recognition. Paper
- [IEEE] Technical approaches to Chinese sign language processing: A review. Paper
- [Arch. Comput. Methods Eng.] Sign Language Recognition Systems: A Decade Systematic Literature Review. Paper
- [Int. J. Mach. Learn. & Cyber.] A review of hand gesture and sign language recognition techniques. Paper
Earlier
- [Advanced Robotics] A Review of Deep Learning-Based Approaches to Sign Language Processing. Paper
- [ArXiv] From Rule-Based Models to Deep Learning Transformers Architectures for Natural Language Processing and Sign Language Translation Systems: Survey, Taxonomy and Performance Evaluation. Paper
- [Research in Computing Science] A Comprehensive Review of Sign Language Translation Technologies Using Linguistic Approaches. Paper
- [Electronics] Sign Language Translation: A Survey of Approaches and Techniques. Paper
- [Expert Syst. Appl.] A survey on Sign Language machine translation. Paper
- [ACM TALLIP] State of the Art of Automation in Sign Language: A Systematic Review. Paper
- [Univ. Access Inf. Soc.] Machine translation from text to sign language: a systematic review. Paper
- [Sensors] Artificial Intelligence Technologies for Sign Language. Paper
- [ACM TALLIP] A Comprehensive Review of Sign Language Production. Paper
- [Expert Syst. Appl.] A survey on recent advances in Sign Language Production. Paper
- [Advanced Robotics] A Review of Deep Learning-Based Approaches to Sign Language Processing. Paper
- [ACM TALLIP] State of the Art of Automation in Sign Language: A Systematic Review. Paper
- [Univ. Access Inf. Soc.] Machine translation from text to sign language: a systematic review. Paper
- [ArXiv] All You Need In Sign Language Production. Paper
- [CVPR] Sign Language Production: A Review. Paper
- [Sensors] Artificial Intelligence Technologies for Sign Language. Paper
- [WACV] Sign Language Recognition: A Large-Scale Multi-View Dataset and Comprehensive Evaluation. Paper
- [ICLR] UNI-SIGN: TOWARD UNIFIED SIGN LANGUAGE UNDERSTANDING AT SCALE. Paper
- [IEEE] Continuous Sign Language Recognition With Multi-Scale Spatial-Temporal Feature Enhancement. Paper
- [CVPR] CLIP-SLA: Parameter-Efficient CLIP Adaptation for Continuous Sign Language Recognition. Paper
- [CVPR] Cross-Modal Consistency Learning for Sign Language Recognition. Paper
- [ICCV] Cross-View Isolated Sign Language Recognition via View Synthesis and Feature Disentanglement. Paper
- [MVA]
MAM-FSDContinuous Sign Language Recognition Based on Motor Attention Mechanism and Frame-Level Self-Distillation. Paper - [FO] Mamba vision models: Automated American sign language recognition. Paper
- [SN] Empowering deaf communication: a novel LSTM model for recognizing Indonesian sign language. Paper
- [ICPR] EMPATH: MediaPipe-Aided Ensemble Learning with Attention-Based Transformers for Accurate Recognition of Bangla Word-Level Sign Language. Paper
- [Neurocomputing]
Swin-MSTPSwin-MSTP: Swin transformer with multi-scale temporal perception for continuous sign language recognition. Paper - [Scientific Reports] Improved feature reduction framework for sign language recognition using autoencoders and adaptive Grey Wolf Optimization. Paper
- [MDPI] Real-Time Norwegian Sign Language Recognition Using MediaPipe and LSTM. Paper
- [ArXiv]
SSLRSSLR: A Semi-Supervised Learning Method for Isolated Sign Language Recognition. Paper - [ArXiv] TSLFormer: A Lightweight Transformer Model for Turkish Sign Language Recognition Using Skeletal Landmarks. Paper
- [ArXiv] SignX: The Foundation Model for Sign Recognition. Paper
- [CVPR]
SignGraphSignGraph: A Sign Sequence is Worth Graphs of Nodes. Paper | Code - [ICEECT]
SLRMPCMCSLRMPCMC: Sign Language Recognition using Mediapipe and Cross-Model Comparison. Paper - [ICME]
XMCCross-Modality Consistency Mining for Continuous Sign Language Recognition with Text-Domain Equivalents. Paper
- [PR] Scalable Frame Resolution for Efficient Continuous Sign Language Recognition. Paper
- [ACM TOMM]
SRMImproving Continuous Sign Language Recognition with Consistency Constraints and Signer Removal. Paper | Code - [TALLIP] Isolated Arabic Sign Language Recognition Using a Transformer-based Model and Landmark Keypoints. Paper
- [IFS]
SLR-YOLOSLR-YOLO: An Improved YOLOv8 Network for Real-Time Sign Language Recognition. Paper - [AJSE]
CRKDContinuous Sign Language Recognition Based on Cross-Resolution Knowledge Distillation. Paper
- [ArXiv]
SignVTCLSignVTCL: Multi-Modal Continuous Sign Language Recognition Enhanced by Visual-Textual Contrastive Learning. Paper
- [AAAI]
SENSelf-Emphasizing Network for Continuous Sign Language Recognition. Paper - [ACM MM]
AdaBrowseAdaBrowse: Adaptive Video Browser for Efficient Continuous Sign Language Recognition. Paper - [ICASSP]
DFConvSelf-Sufficient Framework for Continuous Sign Language Recognition. Paper - [CVPR]
CorrNetContinuous Sign Language Recognition with Correlation Network. Paper | Code - [CVPR]
CTCADistilling Cross-Temporal Contexts for Continuous Sign Language Recognition. Paper - [CVPR]
CVT-SLRCVT-SLR: Contrastive Visual-Textual Transformation for Sign Language Recognition with Variational Alignment. Paper | Code - [CVPR]
NLA-SLRNatural Language-Assisted Sign Language Recognition. Paper | Code - [ICCV]
CoSignCoSign: Exploring Co-Occurrence Signals in Skeleton-Based Continuous Sign Language Recognition. Paper - [ICCV]
C²STC22ST: Cross-Modal Contextualized Sequence Transduction for Continuous Sign Language Recognition. Paper - [ICCV]
Cross-LingImproving Continuous Sign Language Recognition with Cross-Lingual Signs. Paper - [NeurIPS]
TwoStream-SLTTwo-Stream Network for Sign Language Recognition and Translation. Paper
- [AJSE]
TSRNetContinuous Sign Language Recognition via Temporal Super-Resolution Network. Paper - [PR]
mLTSF-NetMulti-Scale Local-Temporal Similarity Fusion for Continuous Sign Language Recognition. Paper - [IEEE TM]
Multilingual-CSLRCollaborative Multilingual Continuous Sign Language Recognition: A Unified Framework. Paper - [IEEE TM]
PA-CMAPrior-Aware Cross Modality Augmentation Learning for Continuous Sign Language Recognition. Paper - [CIS]
STTNSpatial–Temporal Transformer for End-to-End Sign Language Recognition. Paper - [IEEE Access]
BAE-AttentionBoundary-Adaptive Encoder with Attention Method for Chinese Sign Language Recognition. Paper - [AIHC] Continuous Sign Language Recognition Using Isolated Signs Data and Deep Transfer Learning. Paper
- [TPAMI]
SignBERT+SignBERT+: Hand-Model-Aware Self-Supervised Pre-Training for Sign Language Understanding. Paper
- [ISCA]
LCSALocal Context-aware Self-attention for Continuous Sign Language Recognition. Paper - [ECCV]
TLPTemporal Lift Pooling for Continuous Sign Language Recognition. Paper | Code - [ECCV]
RadialCTCDeep Radial Embedding for Visual Sequence Learning. Paper - [CVPR]
C²SLRC2SLR: Consistency-Enhanced Continuous Sign Language Recognition. Paper
- [Sensors]
STAMFNovel Spatio-Temporal Continuous Sign Language Recognition Using an Attentive Multi-Feature Network. Paper - [IEEE SPL]
CA-SignBERTA Cross-Attention BERT-Based Framework for Continuous Sign Language Recognition. Paper
- [ArXiv]
MSTNMulti-View Spatial-Temporal Network for Continuous Sign Language Recognition. Paper - [ArXiv]
MSTNetMulti-Scale Temporal Network for Continuous Sign Language Recognition. Paper
- [ICCV]
VACVisual Alignment Constraint for Continuous Sign Language Recognition. Paper - [ICCV]
SMKDSelf-Mutual Distillation Learning for Continuous Sign Language Recognition. Paper - [IJCNN]
ST-GCNContinuous Sign Language Recognition based on Multi-Part Skeleton Data. Paper - [CVPR] Fingerspelling Detection in American Sign Language. Paper
- [TCSVT]
SBD-RLSemantic Boundary Detection With Reinforcement Learning for Continuous Sign Language Recognition. Paper - [Sensors]
SLRGANContinuous Sign Language Recognition through a Context-Aware Generative Adversarial Network. Paper - [IEEE TM]
PiSLTRcPiSLTRc: Position-Informed Sign Language Transformer with Content-Aware Convolution. Paper - [ESA]
H-GANAn optimized Generative Adversarial Network based continuous sign language classification. Paper - [IEEE TM]
STMC-SLRTSpatial-Temporal Multi-Cue Network for Sign Language Recognition and Translation. Paper - [IEEE Access]
SignBERTSignBERT: A BERT-Based Deep Learning Framework for Continuous Sign Language Recognition. Paper - [IEEE TM]
EnStimCTCA Comprehensive Study on Deep Learning-Based Methods for Sign Language Recognition. Paper
- [ICPR]
ISFTContinuous Sign Language Recognition with Iterative Spatiotemporal Fine-Tuning. Paper - [ECAI]
SAFISelf-Attention-Based Fully-Inception Networks for Continuous Sign Language Recognition. Paper - [ICPR]
SANContext Matters: Self-Attention for Sign Language Recognition. Paper - [ECCV]
SMSStochastic Fine-Grained Labeling of Multi-State Sign Glosses for Continuous Sign Language Recognition. Paper - [ECCV]
FCNFully Convolutional Networks for Continuous Sign Language Recognition. Paper - [ACM MM]
CMAugBoosting Continuous Sign Language Recognition via Cross Modality Augmentation. Paper - [CVPR]
SL-TransfSign Language Transformers: Joint End-to-end Sign Language Recognition and Translation.
Paper | Code - [AAAI]
STMCSpatial-Temporal Multi-Cue Network for Continuous Sign Language Recognition. Paper
- [JCR] Skeleton-Based Chinese Sign Language Recognition and Generation for Bidirectional Communication Between Deaf and Hearing People. Paper
- [TPAMI]
Multi-Stream CLHWeakly Supervised Learning with Multi-Stream CNN-LSTM-HMMs to Discover Sequential Parallelism in Sign Language Videos. Paper - [IEEE Access]
CMA-TEContinuous Sign Language Recognition through Cross-Modal Alignment of Video and Text Embeddings in a Joint-Latent Space. Paper - [Sensors] Recognition of Non-Manual Content in Continuous Japanese Sign Language. Paper
- [MAHCI]
CSLR-PLContinuous Sign Language Recognition Based on Pseudo-Supervised Learning. Paper - [ICIP]
CSLR-RLContinuous Sign Language Recognition via Reinforcement Learning. Paper - [CVPR]
Align-iOptIterative Alignment Network for Continuous Sign Language Recognition. Paper - [ICME]
DPLDDynamic Pseudo Label Decoding for Continuous Sign Language Recognition. Paper - [BigMM]
WIC-NGCDeep Grammatical Multi-classifier for Continuous Sign Language Recognition. Paper - [APSIPA ASC] Exploring RNN-Transducer for Chinese Speech Recognition. Paper
- [IJCAI]
DenseTCNDense Temporal Convolution Network for Sign Language Translation. Paper
- [IEEE TM]
IterativeTrainA Deep Neural Framework for Continuous Sign Language Recognition by Iterative Training. Paper
- [ArXiv]
Sf-netSf-net: Structured feature network for continuous sign language recognition. Paper
- [IJCAI]
DCN-IterativeOptDilated Convolutional Network with Iterative Optimization for Continuous Sign Language Recognition. Paper - [AAAI]
LS-HANVideo-based Sign Language Recognition Without Temporal Segmentation. Paper - [AAAI]
HLSTMHierarchical LSTM for Sign Language Translation. Paper - [CVPRW]
3DRCNNRecognizing American Sign Language Gestures from Within Continuous Videos. Paper
- [CVPR]
ReSignRe-Sign: Re-Aligned End-to-End Sequence Modelling with Deep Recurrent CNN-HMMs. Paper - [ICCV]
SubUNetsSubUNets: End-to-End Hand Shape and Continuous Sign Language Recognition. Paper | Code - [CVPR]
StagedOptRecurrent Convolutional Neural Networks for Continuous Sign Language Recognition by Staged Optimization. Paper - [SenSys]
DeepASLDeepASL: Enabling Ubiquitous and Non-Intrusive Word and Sentence-Level Sign. Paper
- [CMRA]
Openpose-LSTMTowards Continuous Sign Language Recognition with Deep Learning. Paper
- [LREC]
HamNoSys CSLRAutomatic Alignment of HamNoSys Subunits for Continuous Sign Language Recognition. Paper - [BMVC]
Deep SignDeep Sign: Hybrid CNN-HMM for Continuous Sign Language Recognition. Paper
- [COLING]
TextCTC-SLTImprovement in Sign Language Translation Using Text CTC Alignment. Paper | Code - [CVPR] Lost in Translation, Found in Context: Sign Language Translation with Contextual Cues. Paper
- [ArXiv] Bridging Sign and Spoken Languages: Pseudo Gloss Generation for Sign Language Translation. Paper
- [ArXiv] GLoT: A Novel Gated-Logarithmic Transformer for Efficient Sign Language Translation. Paper
- [ECCV]
EVSignEVSign: Sign Language Recognition and Translation with Streaming Events. Paper - [NAACL]
SDDASigner Diversity-driven Data Augmentation for Signer-Independent Sign Language Translation. Paper - [ECAI] Improving Non-autoregressive Sign Language Translation with Random Ordering Progressive Prediction Pre-training.
- [WACV]
HST-GNNSign Language Translation with Hierarchical Spatio-Temporal Graph Neural Network. Paper - [NeurIPS]
TwoStream-SLTTwo-Stream Network for Sign Language Recognition and Translation. Paper - [CVPR]
MMTLBA Simple Multi-Modality Transfer Learning Baseline for Sign Language Translation. Paper
- [Applied Intelligence] Sign language recognition and translation network based on multi-view data. Paper
- [ArXiv] Leveraging Graph-based Cross-modal Information Fusion for Neural Sign Language Translation. Paper
- [CVPR]
BN-TIN-TransfImproving Sign Language Translation with Monolingual Data by Sign Back-Translation. Paper - [MT Summit]
BERT2RNDFrozen Pretrained Transformers for Neural Sign Language Translation. Paper | Code
- [Neurocomputing]
Facial-SLTEnhancing neural sign language translation by highlighting the facial expression information. Paper - [IET] How Important Is Motion in Sign Language Translation? Paper
- [IEEE TMM]
STMC-TSpatial-Temporal Multi-Cue Network for Sign Language Recognition and Translation. Paper
- [ACCV] Understanding Motion in Sign Language: A New Structured Translation Dataset. Paper
- [MDPI] Neural Sign Language Translation Based on Human Keypoint Estimation. Paper
- [CVPR]
NSLTNeural Sign Language Translation. Paper|Code - [ACM MM]
CTFConnectionist Temporal Fusion for Sign Language Translation. Paper
- [WACV]
UniGloRA Spatio-Temporal Representation Learning as an Alternative to Traditional Glosses in Sign Language Translation and Production. Paper | Code - [ICLR]
UNI-SIGNUNI-SIGN: TOWARD UNIFIED SIGN LANGUAGE UNDERSTANDING AT SCALE. Paper|Code - [ACL] Improving Multilingual Sign Language Translation with Automatically Clustered Language Family Information. Paper
- [ArXiv] Spatio-temporal transformer to support automatic sign language translation. Paper
- [ArXiv]
ADATADAT: Time-Series-Aware Adaptive Transformer Architecture for Sign Language Translation. Paper - [ArXiv] Sign Language Translation using Frame and Event Stream: Benchmark Dataset and Algorithms. Paper
- [ArXiv] GLoT: A Novel Gated-Logarithmic Transformer for Efficient Sign Language Translation. Paper
- [ArXiv]
SignMusketeersSignMusketeers: An Efficient Multi-Stream Approach for Sign Language Translation at Scale. Paper
- [NeurIPS] Scaling Sign Language Translation. Paper
- [NeurIPS]
SignCLImproving Gloss-free Sign Language Translation by Reducing Representation Density. Paper | Code - [ACL]
SLT-SEMSign Language Translation with Sentence Embedding Supervision. Paper | Code - [ECCV]
VAPVisual Alignment Pre-training for Sign Language Translation. Paper - [CVPR]
LLM-SLTLLMs Are Good Sign Language Translators. Paper - [LREC-COLING]
SimulSLT-CLTAdaptive Simultaneous Sign Language Translation with Confident Translation Length Estimation. Paper | Code - [LREC-COLING]
FLa-LLMFactorized Learning Assisted with Large Language Model for Gloss-free Sign Language Translation. Paper - [AAAI]
CV-SLTConditional Variational Autoencoder for Sign Language Translation with Cross-Modal Alignment. Paper|Code - [ICASSP]
EMF-SLTAn Explicit Multi-Modal Fusion Method for Sign Language Translation. Paper - [ICLR]
Sign2GPTSign2GPT: Leveraging Large Language Models for Gloss-Free Sign Language Translation. Paper
- [ArXiv]
LLaVA-SLTVisual Language Tuning for Sign Language Translation. Paper - [ArXiv]
SSVP-SLTTowards Privacy-Aware Sign Language Translation at Scale. Paper | Code - [ArXiv] Unsupervised Sign Language Translation and Generation. Paper
- [ArXiv] American Sign Language Video to Text Translation. Paper | Code
- [ArXiv]
Online-CSLRTTowards Online Sign Language Recognition and Translation. Paper | Code - [ArXiv] Improving Gloss-free Sign Language Translation by Reducing Representation Density. Paper
- [ArXiv]
MSKA-SLTMulti-Stream Keypoint Attention Network for Sign Language Recognition and Translation. Paper | Code - [ArXiv]
SignformerSignformer is all you need: Towards Edge AI for Sign Language. Paper - [ArXiv]
C²RLC2RL: Content and Context Representation Learning for Gloss-free Sign Language Translation and Retrieval. Paper
- [CVPR]
GASLTGloss Attention for Gloss-Free Sign Language Translation. Paper|Code - [ICCV]
GFSLT-VLPGloss-free Sign Language Translation: Improving from Visual-Language Pretraining. Paper|Code - [ICCV]
IP-SLTSign Language Translation with Iterative Prototype. Paper - [ICLR]
SLTUNETSLTUNET: A Simple Unified Model for Sign Language Translation. Paper|Code - [IJCAI]
SLT-CNDEfficient Sign Language Translation with a Curriculum-Based Non-Autoregressive Decoder. Paper|Code - [ICASSP]
ConSLTA Token-Level Contrastive Framework for Sign Language Translation. Paper|Code - [CVPRW]
SLT-IVSign Language Translation from Instructional Videos. Paper | Code - [NeurIPS]
YouTube-ASLYouTube-ASL: A Large-Scale, Open-Domain American Sign Language-English Parallel Corpus. Paper
- [ArXiv]
XmDACross-modality Data Augmentation for End-to-End Sign Language Translation. Paper | Code - [ArXiv]
GloFEGloss-Free End-to-End Sign Language Translation. Paper | Code
- [WMT] Spatio-Temporal Sign Language Representation and Translation. Paper
- [WMT] Experimental Machine Translation of the Swiss German Sign Language via 3D augmentation of body keypoints. Paper|Code
- [ACL]
PETPrior knowledge and memory enriched transformer for sign language translation. Paper - [ACM MM]
MC-SLTMC-SLT: Towards Low-Resource Signer-Adaptive Sign Language Translation. Paper - [CVPR]
MLSLTMLSLT: Towards Multilingual Sign Language Translation. Paper - [CVPR]
MMTLBA Simple Multi-Modality Transfer Learning Baseline for Sign Language Translation. Paper - [NAACL]
TIN-SLTExplore More Guidance: A Task-aware Instruction Network for Sign Language Translation Enhanced with Data Augmentation. Paper|Code - [EMNLP]
OpenASLOpen-Domain Sign Language Translation Learned from Online Video. Paper|Code
- [IEEE]
CSGCRConditional Sentence Generation and Cross-Modal Reranking for Sign Language Translation. Paper - [TPAMI] SignNet II: A Transformer-Based Two-Way Sign Language Translation Model. Paper
- [ArXiv] Tackling low-resourced sign language translation: Upc at wmt-slt 22. Paper
TF-H2SSign Language Translation based on Transformers for the How2Sign Dataset. Paper
- [FG] Content4All Open Research Sign Language Translation Datasets. Paper
- [ACM MM]
SimulSLTSimulSLT: End-to-End Simultaneous Sign Language Translation. Paper - [ACM MM] Skeleton-Aware Neural Sign Language Translation. Paper
- [ICCV] Stochastic Transformer Networks with Linear Competing Units: Application to end-to-end SL Translation. Paper
- [ACM TACCESS] Deep Learning Methods for Sign Language Translation. Paper
- [CVPR]
SL-TransfSign Language Transformers: Joint End-to-end Sign Language Recognition and Translation.
Paper | Code - [ECCV]
MCT-SLTMulti-channel Transformers for Multi-articulatory Sign Language Translation. Paper - [FG]
Tokenization-SLTNeural Sign Language Translation by Learning Tokenization. Paper - [NeurIPS]
TspnetTspnet: Hierarchical feature learning via temporal semantic pyramid for sign language translation. Paper|CODE - [ICTC] Robust Keypoint Normalization Method for Korean Sign Language Translation Using Transformer. Paper
- [CIN] An Improved Sign Language Translation Model with Explainable Adaptations for Processing Long Sign Sentences. Paper
- [MDPI AS] Neural Sign Language Translation based on Human Keypoint Estimation. Paper
- [CVPR]
NSLTNeural Sign Language Translation. Paper|Code - [AAAI] Hierarchical LSTM for Sign Language Translation. Paper
- [ECCV]
SignavatarsSignavatars: A Large-Scale 3D Sign Language Holistic Motion Dataset and Benchmark. Paper - [CVPR] Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation. Paper
- [CVPR] Diffusion-Based Continuous Sign Language Generation with Cluster-Specific Fine-Tuning and Motion-Adapted Transformer. Paper
- [ICCV] Signs as Tokens: A Retrieval-Enhanced Multilingual Sign Language Generator. Paper
- [ArXiv]
CNSignBeyond Words: AuralLLM and SignMST-C for Precise Sign Language Production and Bidirectional Accessibility. Paper - [ArXiv] A Transformer-Based Framework for Greek Sign Language Production using Extended Skeletal Motion Representations. Paper
- [ArXiv] Towards AI-driven Sign Language Generation with Non-manual Markers. Paper
- [ArXiv] Text-Driven Diffusion Model for Sign Language Production. Paper
- [ArXiv] Disentangle and Regularize: Sign Language Production with Articulator-Based Disentanglement and Channel-Aware Regularization. Paper
- [CVPR]
Neural Sign ActorsNeural Sign Actors: A Diffusion Model for 3D Sign Language Production from Text. Paper - [WACV] Sign Language Production with Latent Motion Transformer. Paper
- [ECCV]
Spoken2SignA Simple Baseline for Spoken Language to Sign Language Translation with 3D Avatars. Paper - [ECCV]
SignGenSignGen: End-to-End Sign Language Video Generation with Latent Diffusion. Paper - [AAAI]
G2P-DDMG2P-DDM: Generating Sign Pose Sequence from Gloss Sequence with Discrete Diffusion Model. Paper | Project Page - [IEEE FG] A Gloss-free Sign Language Production with Discrete Representation. Paper
- [IEEE FG]
Data-DrivenA Data-Driven Representation for Sign Language Production. Paper
- [TOMM]
GCDMGloss-driven Conditional Diffusion Models for Sign Language Production. Paper
- [ArXiv]
T2S-GPTT2S-GPT: Dynamic Vector Quantization for Autoregressive Sign Language Production from Text. Paper | Project Page - [ArXiv] iSign: A Benchmark for Indian Sign Language Processing. Paper
- [ArXiv]
UniGloRA Spatio-Temporal Representation Learning as an Alternative to Traditional Glosses in Sign Language Translation and Production. Paper | Code - [ArXiv]
LVMCNLinguistics-Vision Monotonic Consistent Network for Sign Language Production. Paper - [ArXiv]
Sign-IDDSign-IDD: Iconicity Disentangled Diffusion for Sign Language Production. Paper | Code - [ArXiv]
MS2SLMS2SL: Multimodal Spoken Data-Driven Continuous Sign Language Production. Paper - [ArXiv]
SignLLMSignLLM: Sign Language Production Large Language Models. Paper - [ArXiv]
Stitching T2PSign Stitching: A Novel Approach to Sign Language Production. Paper
- [NuerIPS] Generative Interpolation of Sign Language Poses using RVQ-VAE. Paper
- [SEM]
IFECEIncluding Facial Expressions in Contextual Embeddings for Sign Language Generation. Paper - [FG]
SignVQNetAutoregressive Sign Language Production: A Gloss-Free Approach with Discrete Representations. Paper | Code
- [ArXiv]
SignDiffSignDiff: Learning Diffusion Models for American Sign Language Production. Paper | Project Page
- [CVPR]
FS-NETSigning at scale: Learning to co-articulate signs for large-scale photo-realistic sign language production. Paper - [ACM]
GEN-OBTGloss Semantic-Enhanced Network with Online Back-Translation for Sign Language Production. Paper - [3DV] There and Back Again: 3D Sign Language Generation from Text Using Back-Translation. Paper
- [IEEE] Spatial–Temporal Graph Transformer With Sign Mesh Regression for Skinned-Based Sign Language Production. Paper
- [ArXiv] Non-Autoregressive Sign Language Production via Knowledge Distillation. Paper
- [ACM MM]
NAT-EATowards Fast and High-Quality Sign Language Production. Paper - [ICCV]
Mixed SIGNalsMixed SIGNals: Sign Language Production via a Mixture of Motion Primitives. Paper - [BMVC]
NSLP-GNon-Autoregressive Sign Language Production with Gaussian Space. Paper
- [IJCV] Continuous 3D Multi-Channel Sign Language Production via Progressive Transformers and Mixture Density Networks. Paper
- [ECCV]
Progressive TransfProgressive transformers for end-to-end sign language production. Paper | Code - [IJCV] Text2Sign: Towards Sign Language Production Using Neural Machine Translation and Generative Adversarial Networks. Paper
- [WACV] Neural Sign Language Synthesis: Words Are Our Glosses. Paper
- [BMCV]
Adversarial TrainingAdversarial Training for Multi-Channel Sign Language Production. Paper
- [INNS] Skeleton-based Chinese sign language recognition and generation for bidirectional communication between deaf and hearing people. Paper
Earlier
- [BMVC 2018] Sign Language Production using Neural Machine Translation and Generative Adversarial Networks. Paper
| Model Name | Year | Architecture | WER | Model Input | Conference/Journal | Code |
|---|---|---|---|---|---|---|
| IterativeTrain | 2019 | CNN + BLSTM | 2.8 | RGB-Frames | IEEE TM | - |
| Re-Sign | 2017 | CNN + BLSTM + HMM | 4.8 | RGB-Frames | CVPR | - |
| Deep Sign | 2016 | CNN + HMM | 7.4 | RGB-Frames | BMVC | - |
| Model Name | Year | Architecture | WER | Model Input | Conference/Journal | Code |
|---|---|---|---|---|---|---|
| Cross-Ling | 2023 | - | 16.7 | RGB-Frames | ICCV | - |
| SignVTCL | 2024 | S3D + CTC + mBART + Adapters | 17.6 | RGB-Frames, Skeleton-Keypoints, Optical Flow | ArXiv | - |
| C²ST | 2023 | - | 17.7 | RGB-Frames | ICCV | - |
| CA-SignBERT | 2022 | (3+2+1)D ResNet + BERT + BLSTM + CTC | 18.6 | RGB-Frames | IEEE SPL | - |
| MAM-FSD | 2025 | CNN + 1DCNN + BSLTM | 18.8 | RGB-Frames | MVA | - |
| TwoStream-SLT | 2023 | S3D + CTC | 18.8 | RGB-Frames, Skeleton-Keypoints | NeurIPS | - |
| MultiSignGraph | 2024 | GCN + KNN | 19.1 | RGB-Frames | CVPR | Available |
| CorrNet | 2023 | CNN + BLSTM | 19.4 | RGB-Frames | CVPR | Available |
| XMC-n | 2024 | - | 19.82 | RGB-Frames | ICME | - |
| STTN | 2023 | Transformer | 19.98 | RGB-Frames | CIS | - |
| SignBERT+ | 2023 | - | 20.0 | Skeleton-Keypoints | TPAMI | - |
| PA-CMA | 2023 | CNN-TCN + BLSTM + CTC | 20.0 | RGB-Frames | IEEE TM | - |
| SignGraph | 2024 | GCN + KNN | 20.1 | RGB-Frames | CVPR | Available |
| CoSign-2s | 2023 | GCN + CNN + BLSTM | 20.1 | RGB-Frames, Skeleton-Keypoints | ICCV | - |
| CVT-SLR | 2023 | CNN + MLP + Self-Attention + CTC | 20.1 | RGB-Frames | CVPR | Available |
| RadialCTC | 2022 | - | 20.2 | RGB-Frames | ECCV | - |
| MultiModal SignBERT | 2021 | (3+2+1)DCNN + BERT + LSTM | 20.2 | RGB-Frames | IEEE Access | - |
| CTCA | 2023 | CNN + 1D-TCN + BLSTM + CTC | 20.3 | RGB-Frames | CVPR | - |
| C²SLR | 2022 | - | 20.4 | RGB-Frames | CVPR | - |
| STMC-SLRT | 2021 | 2D-CNN + TempConv + BLSTM + CTC | 20.7 | RGB-Frames | IEEE TM | - |
| AdaBrowse | 2023 | CNN + BLSTM | 20.7 | RGB-Frames | ACM MM | - |
| DFConv | 2023 | CNN + ME + BLSTM | 20.8 | RGB-Frames | ICASSP | - |
| TLP | 2022 | CNN + BLSTM + CTC | 20.8 | RGB-Frames | ECCV | Available |
| CRKD | 2024 | ResNet50 + 2D-CNN + TSCM-2D CNN + CTC + MSE | 20.9 | RGB-Frames | AJSE | - |
| Multilingual-CSLR | 2023 | CNN + BLSTM + CTC | 20.9 | RGB-Frames | IEEE TM | - |
| SEN | 2023 | CNN + BLSTM | 21.0 | RGB-Frames | AAAI | - |
| SMKD | 2021 | CNN + BLSTM + CTC | 21.0 | RGB-Frames | ICCV | - |
| SignBERT | 2021 | (3+2+1)DCNN + BERT + LSTM | 21.4 | RGB-Frames | IEEE Access | - |
| MSTNet | 2022 | CNN + Transformer | 21.4 | RGB-Frames | ArXiv | - |
| STAMF | 2022 | CNN + MHA + BLSTM + CTC | 21.5 | RGB-Frames, Skeleton-Keypoints | Sensors | - |
| LCSA | 2022 | VGGNet + Transformer | 21.9 | RGB-Frames | ISCA | - |
| CMAug | 2020 | CNN-TCN + LSTM | 21.9 | RGB-Frames | ACM MM | - |
| VAC | 2021 | CNN + BLSTM + CTC | 22.3 | RGB-Frames | ICCV | - |
| MSTN | 2022 | Vit + GCN + Transformer + CTC | 22.8 | RGB-Frames, Skelenton-Keypoints | ICCV | - |
| mLTSF-Net + GFE | 2023 | FCN | 23.0 | RGB-Frames | PR | - |
| PiSLTRc | 2021 | CNN + Transformer | 23.2 | RGB-Frames | IEEE TM | - |
| SLRGAN | 2021 | GAN | 23.4 | RGB-Frames | Sensors | - |
| mLTSF-Net | 2023 | FCN | 23.5 | RGB-Frames | PR | - |
| IterativeTrain + SBD-RL | 2021 | - | 23.5 | RGB-Frames | TCSVT | - |
| FCN | 2020 | FCN + GFE | 23.9 | RGB-Frames | ECCV | - |
| CMA-TE | 2020 | CNN + BLSTM | 24.00 | RGB-Frames | IEEE Access | - |
| IterativeTrain | 2019 | CNN + BLSTM | 24.4 | RGB-Frames | IEEE TM | - |
| TSRNet | 2023 | - | 24.7 | RGB-Frames | AJSE | - |
| SMS | 2020 | 2DCNN + Transformer | 25.3 | RGB-Frames | ECCV | - |
| Multi-Stream CLH | 2020 | Multi-Stream CNN-LSTM-HMM | 26.0 | RGB-Frames | TPAMI | - |
| Re-Sign | 2017 | CNN + BLSTM + HMM | 26.8 | RGB-Frames | CVPR | - |
| SBD-RL | 2021 | CNN + BLSTM + CTC + RL | 28.6 | RGB-Frames | TCSVT | - |
| SAN | 2020 | 2D-CNN + Transformer | 29.7 | RGB-Frames | ICPR | - |
| SAFI | 2020 | (2+1)D-CNN + Self-Attention | 31.3 | RGB-Frames | ECAI | - |
| ISFT | 2020 | (2+1)D-CNN + BLSTM | 34.4 | RGB-Frames | ICPR | - |
| DPLD + TEM | 2019 | I3D-BGRU-CTC | 34.5 | RGB-Frames | ICME | - |
| SF-Net(ResNet-18) | 2019 | 2D3DCNN + LSTM + BLSTM | 34.9 | RGB-Frames | ArXiv | - |
| Align-iOpt | 2019 | 3D-ResNet + BLSTM + Attention-LSTM + CTC | 36.7 | RGB-Frames | CVPR | - |
| DCN-IterativeOpt | 2019 | 3DCNN + CTC | 37.3 | RGB-Frames | IJCAI | - |
| CSLR-RL | 2019 | 3D-ResNet + Transformer | 38.3 | RGB-Frames | ICIP | - |
| LS-HAN | 2018 | CNN + LS + HAN | 38.3 | RGB-Frames | AAAI | - |
| StagedOpt | 2017 | CNN + BLSTM | 38.7 | RGB-Frames | CVPR | - |
| Deep Sign | 2016 | CNN + HMM | 38.8 | RGB-Frames | BMVC | - |
| CSLR-PL | 2019 | 3DCNN + BGRU + CTC | 40.6 | RGB-Frames | MAHCI | - |
| SubUNets | 2017 | CNN + BLSTM | 40.7 | RGB-Frames | ICCV | Avaliable |
| HamNoSys CSLR | 2016 | CNN + HMM | 45.1 | RGB-Frames | LREC | - |
| Model Name | Year | Architecture | WER | Model Input | Conference/Journal | Code |
|---|---|---|---|---|---|---|
| SignVTCL | 2024 | S3D + CTC + mBART + Adapters | 17.9 | RGB-Frames, Skeleton-Keypoints, Optical Flow | ArXiv | - |
| Cross-Ling | 2023 | - | 18.5 | RGB-Frames | ICCV | - |
| C²ST | 2023 | - | 18.9 | RGB-Frames | ICCV | - |
| MultiSignGraph | 2024 | GCN + KNN | 19.1 | RGB-Frames | CVPR | Available |
| TwoStream-SLT | 2023 | S3D + CTC | 19.3 | RGB-Frames, Skeleton-Keypoints | NeurIPS | - |
| MAM-FSD | 2025 | CNN + 1DCNN + BSLTM | 19.4 | RGB-Frames | MVA | - |
| SignBERT+ | 2023 | - | 19.9 | Skeleton-Keypoints | TPAMI | - |
| SignGraph | 2024 | GCN + KNN | 20.0 | RGB-Frames | CVPR | Available |
| PA-CMA | 2023 | CNN-TCN + BLSTM + CTC | 20.0 | RGB-Frames | IEEE TM | - |
| CoSign-2s | 2023 | GCN + CNN + BLSTM | 20.1 | RGB-Frames, Skeleton-Keypoints | ICCV | - |
| C²SLR | 2022 | - | 20.4 | RGB-Frames | CVPR | - |
| CorrNet | 2023 | CNN + BLSTM | 20.5 | RGB-Frames | CVPR | Available |
| SEN | 2023 | CNN + BLSTM | 20.7 | RGB-Frames | AAAI | - |
| TLP | 2022 | CNN + BLSTM + CTC | 21.2 | RGB-Frames | ECCV | Available |
| SMKD | 2021 | CNN + BLSTM + CTC | 22.4 | RGB-Frames | ICCV | - |
| PiSLTRc | 2021 | CNN + Transformer | 22.9 | RGB-Frames | IEEE TM | - |
| Multi-Stream CLH | 2020 | Multi-Stream CNN-LSTM-HMM | 24.1 | RGB-Frames | TPAMI | - |
| CMA-TE | 2020 | CNN + BLSTM | 24.3 | RGB-Frames | IEEE Access | - |
| SL-Transf | 2020 | Transformer | 24.49 | RGB-Frames | CVPR | Avaliable |
| FCN | 2020 | FCN + GFE | 25.1 | RGB-Frames | ECCV | - |
| Model Name | Year | Architecture | WER | Model Input | Conference/Journal | Code |
|---|---|---|---|---|---|---|
| SignVTCL | 2024 | S3D + CTC + mBART + Adapters | 24.1 | RGB-Frames, Skeleton-Keypoints, Optical Flow | ArXiv | - |
| MAM-FSD | 2025 | CNN + 1DCNN + BSLTM | 24.5 | RGB-Frames | MVA | - |
| TwoStream-SLT | 2023 | S3D + CTC | 25.3 | RGB-Frames, Skeleton-Keypoints | NeurIPS | - |
| C²ST | 2023 | - | 25.8 | RGB-Frames | ICCV | - |
| UNI-SIGN | 2025 | RTMPose-x + Spatial-GCN + ST-GCN + EfficientNet-B0 + Prior-Guided Fusion (Multi-head + Deformable Attention + Gate) + mT5-Base + Unified LM Loss (no CTC) | 26.0 | RGB-Frames, Skeleton-Keypoints | ICLR | Avaliable |
| MultiSignGraph | 2024 | GCN + KNN | 26.4 | RGB-Frames | CVPR | Available |
| XMC-d | 2024 | - | 26.4 | RGB-Frames | ICME | - |
| XMC-n | 2024 | - | 26.8 | RGB-Frames | ICME | - |
| CoSign-2s | 2023 | GCN + CNN + BLSTM | 27.2 | RGB-Frames, Skeleton-Keypoints | ICCV | - |
| SignGraph | 2024 | GCN + KNN | 27.4 | RGB-Frames | CVPR | Available |
| PA-CMA | 2023 | CNN-TCN + BLSTM + CTC | 28.7 | RGB-Frames | IEEE TM | - |
| CorrNet | 2023 | CNN + BLSTM | 30.1 | RGB-Frames | CVPR | Available |
| SEN | 2023 | CNN + BLSTM | 30.7 | RGB-Frames | AAAI | - |
| IterativeTrain ✢ | 2019 | CNN + BLSTM | 32.4 | RGB-Frames | IEEE TM | - |
| FCN ✢ | 2020 | FCN + GFE | 32.5 | RGB-Frames | ECCV | - |
| LS-HAN ✢ | 2018 | CNN + LS + HAN | 39.4 | RGB-Frames | AAAI | - |
| SubUNets | 2017 | CNN + BLSTM | 41.0 | RGB-Frames | ICCV | Avaliable |
✢ denotes the results were implemented by BN-TIN-Transf
| Model Name | Year | Architecture | WER | Model Input | Conference/Journal | Code |
|---|---|---|---|---|---|---|
| C²SLR + SRM | 2024 | - | 0.68 | RGB-Frames | ACM TOMM | Available |
| STAMF | 2022 | CNN + MHA + BLSTM + CTC | 0.7 | RGB-Frames, Skeleton-Keypoints | Sensors | - |
| MSTNet | 2022 | CNN + Transformer | 0.7 | RGB-Frames | ArXiv | - |
| CorrNet | 2023 | CNN + BLSTM | 0.8 | RGB-Frames | CVPR | Available |
| SEN | 2023 | CNN + BLSTM | 0.8 | RGB-Frames | AAAI | - |
| C²SLR | 2022 | - | 0.9 | RGB-Frames | CVPR | - |
| CA-SignBERT | 2022 | (3+2+1)D ResNet + BERT + BLSTM + CTC | 1.14 | RGB-Frames | IEEE SPL | - |
| STTN | 2023 | Transformer | 1.2 | RGB-Frames | CIS | - |
| ST-GCN | 2021 | GCN + BLSTM + LSTM | 1.3 | RGB-Frames | IJCNN | - |
| LCSA | 2022 | VGGNet + Transformer | 1.4 | RGB-Frames | ISCA | - |
| MultiModal SignBERT | 2021 | (3+2+1)DCNN + BERT + LSTM | 1.52 | RGB-Frames | IEEE Access | - |
| VAC | 2021 | CNN + BLSTM + CTC | 1.6 | RGB-Frames | ICCV | - |
| MSTN | 2022 | Vit + GCN + Transformer + CTC | 1.9 | RGB-Frames, Skelenton-Keypoints | ICCV | - |
| STMC | 2020 | CNN + BLSTM + CTC | 2.1 | RGB-Frames | AAAI | - |
| SignBERT | 2021 | (3+2+1)DCNN + BERT + LSTM | 2.26 | RGB-Frames | IEEE Access | - |
| CMA-TE | 2020 | CNN + BLSTM | 2.4 | RGB-Frames | IEEE Access | - |
| EnStimCTC | 2021 | - | 2.41 | RGB-Frames | IEEE TM | - |
| mLTSF-Net | 2023 | FCN | 2.5 | RGB-Frames | PR | - |
| CRKD | 2024 | ResNet50 + 2D-CNN + TSCM-2D CNN + CTC + MSE | 2.6 | RGB-Frames | AJSE | - |
| PiSLTRc | 2021 | CNN + Transformer | 2.8 | RGB-Frames | IEEE TM | - |
| FCN | 2020 | FCN + GFE | 3.0 | RGB-Frames | ECCV | - |
| SF-Net(ResNet-18) | 2019 | 2D3DCNN + LSTM + BLSTM | 3.8 | RGB-Frames | ArXiv | - |
| DPLD + TEM | 2019 | I3D-BGRU-CTC | 4.7 | RGB-Frames | ICME | - |
| DPLD | 2019 | I3D-BGRU-CTC | 5.6 | RGB-Frames | ICME | - |
| HLSTM-atten | 2018 | 3D-CNN + LSTM | 10.2 | RGB-Frames | AAAI | - |
| HLSTM | 2018 | 3D-CNN + LSTM | 10.7 | RGB-Frames | AAAI | - |
| CTF | 2018 | C3D-ResNet + TConv + BGRU + CTC | 11.2 | RGB-Frames | ACM MM | - |
| Model Name | Year | Architecture | WER | Model Input | Conference/Journal | Code |
|---|---|---|---|---|---|---|
| CA-SignBERT | 2022 | (3+2+1)D ResNet + BERT + BLSTM + CTC | 19.80 | RGB-Frames | IEEE SPL | - |
| SignBERT | 2021 | (3+2+1)DCNN + BERT + LSTM | 24.90 | RGB-Frames | IEEE Access | - |
| STMC | 2020 | CNN + BLSTM + CTC | 28.6 | RGB-Frames | AAAI | - |
| Align-iOpt | 2019 | 3D-ResNet + BLSTM + Attention-LSTM + CTC | 32.7 | RGB-Frames | CVPR | - |
| WIC-NGC | 2019 | 3D-ResNet + BLSTM | 50.9 | RGB-Frames | BigMM | - |
| Model Name | Year | BLEU-4 | Model Input | Conference/Journal | Code |
|---|---|---|---|---|---|
| TextCTC-SLT | 2025 | 28.42 | RGB-Frames | COLING | Available |
| TwoStream-SLT | 2022 | 26.71 | RGB-Frames, Skeleton-Keypoints | NeurIPS | - |
| SLTUNET | 2023 | 26.00 | RGB-Frames | ICLR | Avaliable |
| ConSLT | 2023 | 25.48 | RGB-Frames | ICASSP | Avaliable |
| MMTLB | 2022 | 24.60 | RGB-Frames | CVPR | - |
| STMC-Transf | 2020 | 24.00 | RGB-Frames | ArXiv | Avaliable |
| STMC-T | 2021 | 23.65 | RGB-Frames | IEEE TMM | - |
| BN-TIN-Transf + BT | 2021 | 23.51 | RGB-Frames | CVPR | - |
| SimulSLT | 2021 | 23.14 | RGB-Frames | ACM MM | - |
| BN-TIN-Transf | 2021 | 22.54 | RGB-Frames | CVPR | - |
| BERT2RND | 2021 | 22.47 | RGB-Frames | MT Summit | Avaliable |
| SL-Transf | 2020 | 22.45 | RGB-Frames | CVPR | Avaliable |
| HST-GNN | 2022 | 22.3 | RGB-Frames | WACV | - |
| NSLT | 2018 | 18.13 | RGB-Frames | CVPR | Avaliable |
| Facial-SLT | 2021 | 10.89 | RGB-Frames | Neurocomputing | - |
| Model Name | Year | BLEU-4 | Model Input | Conference/Journal | Code |
|---|---|---|---|---|---|
| CV-SLT | 2022 | 29.27 | RGB-Frames | AAAI | Avaliable |
| MSKA-SLT | 2024 | 29.03 | Skeleton-Keypoints | ArXiv | Avaliable |
| TwoStream-SLT | 2022 | 28.95 | RGB-Frames, Skeleton-Keypoints | NeurIPS | - |
| SLTUNET | 2023 | 28.47 | RGB-Frames | ICLR | Avaliable |
| MMTLB | 2022 | 28.39 | RGB-Frames | CVPR | - |
| IP-SLT | 2023 | 27.97 | RGB-Frames | ICCV | - |
| C²RL | 2024 | 26.75 | RGB-Frames | ArXiv | - |
| VAP | 2024 | 26.16 | RGB-Frames | ECCV | - |
| EMF-SLT | 2024 | 26.01 | RGB-Frames | ICASSP | - |
| SignBERT+ | 2023 | 25.70 | Skeleton-Keypoints | TPAMI | - |
| XmDA | 2023 | 25.36 | RGB-Frames | ArXiv | Avaliable |
| SLT-CND | 2023 | 24.71 | RGB-Frames | IJCAI | Avaliable |
| BN-TIN-Transf + BT | 2021 | 24.32 | RGB-Frames | CVPR | - |
| SimulSLT-CTL | 2024 | 24.20 | RGB-Frames | LREC-COLING | Avaliable |
| SLT-SEM | 2024 | 24.12 | RGB-Frames | ACL | - |
| PET | 2022 | 24.02 | RGB-Frames | ICLR | - |
| SimulSLT-CTL++ | 2024 | 23.75 | RGB-Frames | LREC-COLING | Avaliable |
| Online-CSLRT | 2024 | 23.69 | RGB-Frames | ArXiv | Avaliable |
| Signformer | 2024 | 23.43 | RGB-Frames | ArXiv | - |
| LLaVA-SLT | 2024 | 23.43 | RGB-Frames | ArXiv | - |
| LLM-SLT | 2024 | 23.40 | RGB-Frames | CVPR | - |
| FLa-LLM | 2024 | 23.09 | RGB-Frames | LREC-COLING | - |
| SignCL | 2024 | 22.74 | RGB-Frames | NeurIPS | Available |
| Sign2GPT | 2024 | 22.52 | RGB-Frames | ArXiv | - |
| BN-TIN-Transf | 2021 | 21.68 | RGB-Frames | CVPR | - |
| ConSLT | 2023 | 21.59 | RGB-Frames | ICASSP | Avaliable |
| GFSLT-VLP | 2023 | 21.44 | RGB-Frames | ICCV | Avaliable |
| SL-Transf | 2020 | 21.32 | RGB-Frames | CVPR | Avaliable |
| MCT-SLT | 2020 | 18.30 | RGB-Frames | ECCV | - |
| GASLT | 2023 | 15.74 | RGB-Frames | CVPR | Avaliable |
| CSGCR | 2022 | 15.18 | RGB-Frames | IEEE | - |
| Tspnet | 2020 | 13.41 | RGB-Frames | NeurIPS | Avaliable |
| Tokenization-SLT | 2020 | 13.25 | RGB-Frames | FG | - |
| UniGloR | 2024 | 12.86 | RGB-Frames | ArXiv | - |
| SimulSLT | 2021 | 12.27 | RGB-Frames | ACM MM | - |
| NSLT | 2018 | 9.58 | RGB-Frames | CVPR | Avaliable |
| Model Name | Year | BLEU-4 | Model Input | Conference/Journal | Code |
|---|---|---|---|---|---|
| TwoStream-SLT | 2022 | 25.79 | RGB-Frames, Skeleton-Keypoints | NeurIPS | - |
| SLTUNET | 2023 | 23.76 | RGB-Frames | ICLR | Avaliable |
| TextCTC-SLT | 2025 | 22.47 | RGB-Frames | COLING | Available |
| MMTLB | 2022 | 21.46 | RGB-Frames | CVPR | - |
| BN-TIN-Transf + BT | 2021 | 19.67 | RGB-Frames | CVPR | - |
| HST-GNN | 2022 | 17.8 | RGB-Frames | WACV | - |
| BN-TIN-Transf | 2021 | 16.25 | RGB-Frames | CVPR | - |
| NSLT + Luong ✦ | 2018 | 11.03 | RGB-Frames | CVPR | Avaliable |
| Model Name | Year | BLEU-4 | Model Input | Conference/Journal | Code |
|---|---|---|---|---|---|
| UNI-SIGN | 2025 | 26.36 | RGB-Frames, Skeleton-Keypoints | ICLR | Avaliable |
| MSKA-SLT | 2024 | 25.52 | Skeleton-Keypoints | ArXiv | Avaliable |
| TwoStream-SLT | 2022 | 25.42 | RGB-Frames, Skeleton-Keypoints | NeurIPS | - |
| SLTUNET | 2023 | 25.01 | RGB-Frames | ICLR | Avaliable |
| MMTLB | 2022 | 23.92 | RGB-Frames | CVPR | - |
| C²RL | 2024 | 21.61 | RGB-Frames | ArXiv | - |
| XmDA | 2023 | 21.58 | RGB-Frames | ArXiv | Avaliable |
| BN-TIN-Transf + BT | 2021 | 21. 34 | RGB-Frames | CVPR | - |
| VAP | 2024 | 20.85 | RGB-Frames | ECCV | - |
| LLaVA-SLT | 2024 | 20.42 | RGB-Frames | ArXiv | - |
| IP-SLT | 2023 | 16.72 | RGB-Frames | ICCV | - |
| SLT-CND | 2023 | 16.61 | RGB-Frames | IJCAI | Avaliable |
| SignCL | 2024 | 16.16 | RGB-Frames | NeurIPS | Available |
| LLM-SLT | 2024 | 15.75 | RGB-Frames | CVPR | - |
| Sign2GPT | 2024 | 15.40 | RGB-Frames | ArXiv | - |
| ConSLT | 2023 | 14.53 | RGB-Frames | ICASSP | Avaliable |
| FLa-LLM | 2024 | 14.20 | RGB-Frames | LREC-COLING | - |
| BN-TIN-Transf | 2021 | 13.19 | RGB-Frames | CVPR | - |
| GFSLT-VLP | 2023 | 11.00 | RGB-Frames | ICCV | Avaliable |
| NSLT + Luong ✦ | 2018 | 7.56 | RGB-Frames | CVPR | Avaliable |
| GASLT | 2023 | 4.07 | RGB-Frames | CVPR | Avaliable |
| SL-Transf ❉ | 2020 | 3.03 | RGB-Frames | CVPR | Avaliable |
| Tspnet ★ | 2020 | 2.97 | RGB-Frames | NeurIPS | Avaliable |
✦ denotes results reproduced by BN-TIN-Transf
❉ denotes results reproduced by GFSLT-VLP
★ denotes results reproduced by GASLT
| Model Name | Year | BLEU-4 | Model Input | Conference/Journal | Code |
|---|---|---|---|---|---|
| SSVP-SLT-LSP | 2024 | 15.5 | RGB-Frames | ArXiv | Avaliable |
| UNI-SIGN | 2025 | 14.9 | RGB-Frames, Skeleton-Keypoints | ICLR | Avaliable |
| SignMusketeers | 2024 | 14.3 | Face & Left/Right Hand RGB crops, Skeleton-Keypoints | ArXiv | Avaliable |
| VAP | 2024 | 12.87 | RGB-Frames | ECCV | - |
| YouTube-ASL | 2024 | 12.39 | RGB-Frames | NeurIPS | - |
| SLT-SEM | 2024 | 11.7 | RGB-Frames | ACL | Avaliable |
| FLa-LLM | 2024 | 9.66 | RGB-Frames | LREC-COLING | - |
| SLT-IV | 2023 | 8.03 | RGB-Frames | CVPRW | Avaliable |
| GloFE-VN | 2023 | 2.24 | RGB-Frames | ArXiv | Avaliable |
| UniGloR | 2024 | 2.22 | RGB-Frames | ArXiv | - |
| TF-H2S | 2022 | 2.21 | RGB-Frames | - | - |
| Model Name | Year | BLEU-4 | Model Input | Conference/Journal | Code |
|---|---|---|---|---|---|
| C²RL | 2024 | 13.21 | RGB-Frames | ArXiv | - |
| GloFE-VN | 2023 | 7.06 | RGB-Frames | ArXiv | Avaliable |
| OpenASL | 2022 | 6.72 | RGB-Frames | EMNLP | Avaliable |
| I3D-Transformer | 2022 | 5.66 | RGB-Frames | - | - |
| NSLT ❒ | 2018 | 4.58 | RGB-Frames | CVPR | Avaliable |
❒ denotes results reproduced by OpenASL
| Model Name | Year | BLEU-4 | WER | DTW-P | Conference/Journal | Code |
|---|---|---|---|---|---|---|
| FS-NET | 2022 | 18.78 | - | - | CVPR | - |
| Adversarial Training | 2020 | 11.7 | - | - | BMVC | - |
| Progressive Transf | 2020 | 10.43 | - | - | ECCV | Avaliable |
| NSLP-G | 2021 | 9.39 | - | - | BMVC | - |
| LVMCN | 2024 | 9.36 | - | 10.14 | ArXiv | - |
| Data-Driven | 2024 | 9.17 | - | - | SEM | - |
| Sign-IDD | 2024 | 9.08 | - | - | ArXiv | - |
| GEN-OBT | 2022 | 8.01 | 81.78 | 10.07 | ACM | - |
| GCDM | 2024 | 7.91 | 81.94 | 11.10 | ACM | - |
| G2P-DDM | 2024 | 7.50 | - | - | AAAI | - |
| NAT-EA | 2021 | 6.66 | 82.01 | - | ACM MM | - |
| NAT-AT | 2021 | 5.53 | 88.15 | - | ACM | - |
| Model Name | Year | BLEU-4 | DTW-P | with Gloss | Conference/Journal | Code |
|---|---|---|---|---|---|---|
| Spoken2Sign | 2024 | 25.46 | - | ✅ | ECCV | - |
| SignDiff | 2023 | 22.15 | - | ❌ | ArXiv | - |
| FS-NET | 2022 | 21.10 | - | ❌ | CVPR | - |
| SignGen | 2024 | 19.71 | - | ❌ | ECCV | - |
| T2S-GPT | 2024 | 11.87 | - | ❌ | ArXiv | - |
| NSLP-G (+ Finetuning) | 2021 | 11.07 | - | ❌ | BMVC | - |
| NSLP-G | 2021 | 10.95 | - | ❌ | BMVC | - |
| Adversarial Training | 2020 | 10.81 | - | ❌ | BMVC | - |
| Progressive Transf | 2020 | 10.51 | - | ❌ | ECCV | Avaliable |
| Progressive Transf | 2020 | 9.68 | - | ✅ | ECCV | Avaliable |
| Data-Driven | 2024 | 9.20 | - | ❌ | SEM | - |
| IFECE (MFs) | 2023 | 8.19 | - | ✅ | SEM | - |
| SignVQNet | 2024 | 6.85 | - | ❌ | FG | - |
| IFECE (MFs + FI + AUs) | 2023 | 5.76 | - | ✅ | SEM | - |
| MS2SL | 2024 | 4.26 | - | ❌ | ArXiv | - |
| Model Name | Year | BLEU-4 | DTW-P | with Gloss | Conference/Journal | Code |
|---|---|---|---|---|---|---|
| Spoken2Sign | 2024 | 21.44 | - | - | ✅ | ECCV |
CVPR 2025 SLRTP2025 Sign Language Production Challenge
- Challenge Summary Papar: SLRTP2025 Sign Language Production Challenge: Methodology, Results and Future Work
- Please refer to this page for more information.