SOTAVerified

Sign Language Recognition

Sign Language Recognition is a computer vision and natural language processing task that involves automatically recognizing and translating sign language gestures into written or spoken language. The goal of sign language recognition is to develop algorithms that can understand and interpret sign language, enabling people who use sign language as their primary mode of communication to communicate more easily with non-signers.

( Image credit: Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison )

Papers

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Showing 51–100 of 297 papers

TitleStatusHype
ASL-Homework-RGBD Dataset: An annotated dataset of 45 fluent and non-fluent signers performing American Sign Language homeworks—0
ASL Citizen: A Community-Sourced Dataset for Advancing Isolated Sign Language Recognition—0
A Hong Kong Sign Language Corpus Collected from Sign-interpreted TV News—0
Generative Multi-Stream Architecture For American Sign Language Recognition—0
Breaking the Barriers: Video Vision Transformers for Word-Level Sign Language Recognition—0
BosphorusSign: A Turkish Sign Language Recognition Corpus in Health and Finance Domains—0
C2ST: Cross-Modal Contextualized Sequence Transduction for Continuous Sign Language Recognition—0
ChaLearn LAP Large Scale Signer Independent Isolated Sign Language Recognition Challenge: Design, Results and Future Research—0
Challenges with Sign Language Datasets for Sign Language Recognition and Translation—0
ASL-Skeleton3D and ASL-Phono: Two Novel Datasets for the American Sign Language—0
Combining Efficient and Precise Sign Language Recognition: Good pose estimation library is all you need—0
Comparison of Autoencoders for tokenization of ASL datasets—0
BosphorusSign22k Sign Language Recognition Dataset—0
A Sign Language Recognition System with Pepper, Lightweight-Transformer, and LLM—0
Advanced Arabic Alphabet Sign Language Recognition Using Transfer Learning and Transformer Models—0
Boosting Continuous Sign Language Recognition via Cross Modality Augmentation—0
Enhancing Mathematics Learning for Hard-of-Hearing Students Through Real-Time Palestinian Sign Language Recognition: A New Dataset—0
3D Face Tracking and Multi-Scale, Spatio-temporal Analysis of Linguistically Significant Facial Expressions and Head Positions in ASL—0
Beyond Words: AuralLLM and SignMST-C for Precise Sign Language Production and Bidirectional Accessibility—0
BEST: BERT Pre-Training for Sign Language Recognition with Coupling Tokenization—0
A Comparative Study of Continuous Sign Language Recognition Techniques—0
FineHand: Learning Hand Shapes for American Sign Language Recognition—0
Fine-Tuning Video Transformers for Word-Level Bangla Sign Language: A Comparative Analysis for Classification Tasks—0
Generative Sign-description Prompts with Multi-positive Contrastive Learning for Sign Language Recognition—0
Bengali Sign Language Recognition through Hand Pose Estimation using Multi-Branch Spatial-Temporal Attention Model—0
BdSLW401: Transformer-Based Word-Level Bangla Sign Language Recognition Using Relative Quantization Encoding (RQE)—0
A platform-independent user-friendly dictionary from Italian to LIS—0
BAUST Lipi: A BdSL Dataset with Deep Learning Based Bangla Sign Language Recognition—0
Bangla sign language recognition using concatenated BdSL network—0
APALU: A Trainable, Adaptive Activation Function for Deep Learning Networks—0
A Comparative Analysis of Techniques and Algorithms for Recognising Sign Language—0
Deep Learning Recognition for Arabic Alphabet Sign Language RGB Dataset—0
Deep Hand: How to Train a CNN on 1 Million Hand Images When Your Data Is Continuous and Weakly Labelled—0
Bangla sign digits recognition using depth information—0
Cross-Language Transfer Learning using Visual Information for Automatic Sign Gesture Recognition—0
An Open Web Platform for Rule-Based Speech-to-Sign Translation—0
Deep Neural Network-Based Sign Language Recognition: A Comprehensive Approach Using Transfer Learning with Explainability—0
Deep Radial Embedding for Visual Sequence Learning—0
Dense Temporal Convolution Network for Sign Language Translation—0
Design of Arabic Sign Language Recognition Model—0
Distilling Cross-Temporal Contexts for Continuous Sign Language Recognition—0
A Dataset for Linguistic Understanding, Visual Evaluation, and Recognition of Sign Languages: The K-RSL—0
Efficient sign language recognition system and dataset creation method based on deep learning and image processing—0
Egyptian Sign Language Recognition Using CNN and LSTM—0
Coupling Natural Language Processing and Animation Synthesis in Portuguese Sign Language Translation—0
End-To-End Sign Language Translation via Multitask Learning—0
Enhanced dynamic sign language recognition using slowfast networks—0
Enhancing Brazilian Sign Language Recognition through Skeleton Image Representation—0
CoSign: Exploring Co-occurrence Signals in Skeleton-based Continuous Sign Language Recognition—0
AUTSL: A Large Scale Multi-modal Turkish Sign Language Dataset and Baseline Methods—0
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All datasetsRWTH-PHOENIX-Weather 2014RWTH-PHOENIX-Weather 2014 TCSL-DailyAUTSLWLASL-2000WLASL100ChicagoFSWildLSA64ZnakiMSASL-1000WLASLBOBSL

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SubUNetsWord Error Rate (WER)40.7—Unverified
2CTF-MMWord Error Rate (WER)37.8—Unverified
3DTNWord Error Rate (WER)36.5—Unverified
4SANWord Error Rate (WER)29.7—Unverified
5Stochastic CSLRWord Error Rate (WER)25.3—Unverified
6CrossModalWord Error Rate (WER)24—Unverified
7SLRGANWord Error Rate (WER)23.4—Unverified
8DNFWord Error Rate (WER)22.86—Unverified
9MSKA-SLRWord Error Rate (WER)22.1—Unverified
10VACWord Error Rate (WER)22.1—Unverified
#ModelMetricClaimedVerifiedStatus
1Stochastic CSLRWord Error Rate (WER)26.1—Unverified
2CrossModalWord Error Rate (WER)24.3—Unverified
3SignBTWord Error Rate (WER)23.9—Unverified
4MMTLBWord Error Rate (WER)22.45—Unverified
5SMKDWord Error Rate (WER)22.4—Unverified
6STMCWord Error Rate (WER)21—Unverified
7WRNN + LETWord Error Rate (WER)20.73—Unverified
8MSKA-SLRWord Error Rate (WER)20.5—Unverified
9C2SLRWord Error Rate (WER)20.4—Unverified
10SignBERT+Word Error Rate (WER)19.9—Unverified
#ModelMetricClaimedVerifiedStatus
1BN-TIN+Transf.Word Error Rate (WER)33.1—Unverified
2C2SLRWord Error Rate (WER)31—Unverified
3SENWord Error Rate (WER)30.7—Unverified
4AdaBrowseWord Error Rate (WER)30.6—Unverified
5CorrNetWord Error Rate (WER)30.1—Unverified
6CTCAWord Error Rate (WER)29.4—Unverified
7TCNetWord Error Rate (WER)29.3—Unverified
8CorrNet+ACDRWord Error Rate (WER)29—Unverified
9MSKA-SLRWord Error Rate (WER)27.8—Unverified
10Swin-MSTPWord Error Rate (WER)27.1—Unverified
#ModelMetricClaimedVerifiedStatus
1STF+LSTMRank-1 Recognition Rate0.99—Unverified
2SAM-SLR (RGB-D)Rank-1 Recognition Rate0.99—Unverified
33D-DCNN + ST-MGCNRank-1 Recognition Rate0.98—Unverified
4Ensemble - NTISRank-1 Recognition Rate0.96—Unverified
5HWGATRank-1 Recognition Rate0.96—Unverified
6MViT-SLRRank-1 Recognition Rate0.96—Unverified
7FE+LSTMRank-1 Recognition Rate0.93—Unverified
8VTN-PFRank-1 Recognition Rate0.93—Unverified
9CNN+FPM+BLSTM+Attention (RGB-D)Rank-1 Recognition Rate0.62—Unverified
#ModelMetricClaimedVerifiedStatus
1Logos-PretrainingTop-1 Accuracy66.82—Unverified
2Uni-SignTop-1 Accuracy63.52—Unverified
3NLA-SLRTop-1 Accuracy61.26—Unverified
4StepNetTop-1 Accuracy61.17—Unverified
5SAM-SLRTop-1 Accuracy58.73—Unverified
6SWIN-SLRTop-1 Accuracy58.51—Unverified
7HWGATTop-1 Accuracy48.49—Unverified
8I3D (pretraining: BSL-1K)Top-1 Accuracy46.82—Unverified
9I3DTop-1 Accuracy32.48—Unverified
#ModelMetricClaimedVerifiedStatus
1Uni-SignTop-1 Accuracy92.25—Unverified
2SiformerTop-1 Accuracy86.5—Unverified
3SignBERTTop-1 Accuracy83.3—Unverified
4I3D, ST-GCNTop-1 Accuracy81.38—Unverified
5StepNetTop-1 Accuracy78.29—Unverified
6I3DTop-1 Accuracy65.89—Unverified
7SPOTERTop-1 Accuracy63.18—Unverified
#ModelMetricClaimedVerifiedStatus
1HandReader_RGBCER (%)30.7—Unverified
2HandReader_KPCER (%)28—Unverified
3HandReader_RGBCER (%)27.6—Unverified
4HandReader_RGB_KPCER (%)27.1—Unverified
5HandReader_KPCER (%)26.2—Unverified
6HandReader_RGB+KPCER (%)24.4—Unverified
#ModelMetricClaimedVerifiedStatus
1SPOTERAccuracy (%)100—Unverified
2SiformerAccuracy (%)99.84—Unverified
3HWGATAccuracy (%)98.59—Unverified
4Bag of words fusion of hand pose/movement/positionAccuracy (%)97—Unverified
53DGCNAccuracy (%)94.84—Unverified
#ModelMetricClaimedVerifiedStatus
1HandReader_RGBCER (%)7.61—Unverified
2HandReader_KPCER (%)7.35—Unverified
3HandReader_RGB_KPCER (%)5.06—Unverified
#ModelMetricClaimedVerifiedStatus
1Uni-SignP-I Top-1 Accuracy78.16—Unverified
2SignBERT+P-I Top-1 Accuracy73.71—Unverified
#ModelMetricClaimedVerifiedStatus
1StepNetTop-1 Accuracy61.17—Unverified
2SignBERT+Top-1 Accuracy55.59—Unverified
#ModelMetricClaimedVerifiedStatus
1StepNetActions Top-177.1—Unverified
#ModelMetricClaimedVerifiedStatus
1MobileNetV2_TSMAccuracy (Top-1)83.6—Unverified
#ModelMetricClaimedVerifiedStatus
1HWGATTop-1 Accuracy93.86—Unverified
#ModelMetricClaimedVerifiedStatus
13D-DCNN + ST-MGCNRank-1 Recognition Rate0.98—Unverified
#ModelMetricClaimedVerifiedStatus
1Skeleton Image RepresentationAccuracy82—Unverified
#ModelMetricClaimedVerifiedStatus
1Skeleton Image RepresentationAccuracy93—Unverified
#ModelMetricClaimedVerifiedStatus
1mVITv2-SMean Accuracy64.09—Unverified