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

Showing 251–297 of 297 papers

TitleStatusHype
Iterative Alignment Network for Continuous Sign Language Recognition—0
Dense Temporal Convolution Network for Sign Language Translation—0
Temporal Unet: Sample Level Human Action Recognition using WiFiCode0
Spatial-Temporal Graph Convolutional Networks for Sign Language Recognition—0
MS-ASL: A Large-Scale Data Set and Benchmark for Understanding American Sign Language—0
American Sign Language fingerspelling recognition in the wild—0
Connectionist Temporal Fusion for Sign Language Translation—0
Improved Techniques for Adversarial Discriminative Domain Adaptation—0
Neural Sign Language TranslationCode0
Optimization of Transfer Learning for Sign Language Recognition Targeting Mobile Platform—0
SMILE Swiss German Sign Language Dataset—0
Video-based Sign Language Recognition without Temporal Segmentation—0
A Study of Convolutional Architectures for Handshape Recognition applied to Sign LanguageCode0
SubUNets: End-To-End Hand Shape and Continuous Sign Language RecognitionCode0
Re-Sign: Re-Aligned End-To-End Sequence Modelling With Deep Recurrent CNN-HMMs—0
Recurrent Convolutional Neural Networks for Continuous Sign Language Recognition by Staged Optimization—0
Learning to Estimate 3D Hand Pose from Single RGB ImagesCode0
Sign Language Recognition Using Temporal Classification—0
Sign Language Recognition Without Frame-Sequencing Constraints: A Proof of Concept on the Argentinian Sign Language—0
Spatial Relationship Based Features for Indian Sign Language Recognition—0
An Open Web Platform for Rule-Based Speech-to-Sign Translation—0
Reasoning about Body-Parts Relations for Sign Language Recognition—0
Deep Hand: How to Train a CNN on 1 Million Hand Images When Your Data Is Continuous and Weakly Labelled—0
BosphorusSign: A Turkish Sign Language Recognition Corpus in Health and Finance Domains—0
Modeling Time Series Similarity with Siamese Recurrent Networks—0
Evaluation of Deep Learning based Pose Estimation for Sign Language Recognition—0
Real-time Sign Language Fingerspelling Recognition using Convolutional Neural Networks from Depth mapCode0
Contour-based Hand Pose Recognition for Sign Language Recognition—0
Coupling Natural Language Processing and Animation Synthesis in Portuguese Sign Language Translation—0
Sign Language Fingerspelling Classification from Depth and Color Images using a Deep Belief Network—0
Visual Speech Recognition—0
Real-Time and Robust Method for Hand Gesture Recognition System Based on Cross-Correlation Coefficient—0
Improvement Tracking Dynamic Programming using Replication Function for Continuous Sign Language Recognition—0
Unsupervised Feature Learning for Visual Sign Language Identification—0
A New Framework for Sign Language Recognition based on 3D Handshape Identification and Linguistic Modeling—0
SLMotion - An extensible sign language oriented video analysis tool—0
Extensions of the Sign Language Recognition and Translation Corpus RWTH-PHOENIX-Weather—0
3D Face Tracking and Multi-Scale, Spatio-temporal Analysis of Linguistically Significant Facial Expressions and Head Positions in ASL—0
Robust Feature Extraction to Utterance Fluctuation of Articulation Disorders Based on Random Projection—0
Improving Continuous Sign Language Recognition: Speech Recognition Techniques and System Design—0
Recognition of Indian Sign Language in Live Video—0
Pixel-Level Hand Detection in Ego-centric Videos—0
Extension of hidden markov model for recognizing large vocabulary of sign language—0
Un syst\`eme de segmentation automatique de gestes appliqu\'e \`a la Langue des Signes (An automatic gesture segmentation system applied to Sign Language) [in French]—0
Recognition of Nonmanual Markers in American Sign Language (ASL) Using Non-Parametric Adaptive 2D-3D Face Tracking—0
A platform-independent user-friendly dictionary from Italian to LIS—0
RWTH-PHOENIX-Weather: A Large Vocabulary Sign Language Recognition and Translation Corpus—0
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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
9VACWord Error Rate (WER)22.1—Unverified
10MSKA-SLRWord 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