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 151–200 of 297 papers

TitleStatusHype
StepNet: Spatial-temporal Part-aware Network for Isolated Sign Language Recognition—0
A Classification Model Utilizing Facial Landmark Tracking to Determine Sentence Types for American Sign Language Recognition—0
Sentence-Level Sign Language Recognition Framework—0
Deep Radial Embedding for Visual Sequence Learning—0
Temporal superimposed crossover module for effective continuous sign language—0
Two-Stream Network for Sign Language Recognition and Translation—0
Signing Outside the Studio: Benchmarking Background Robustness for Continuous Sign Language RecognitionCode0
ArabSign: A Multi-modality Dataset and Benchmark for Continuous Arabic Sign Language RecognitionCode0
Hierarchical I3D for Sign Spotting—0
Combining Efficient and Precise Sign Language Recognition: Good pose estimation library is all you need—0
An Efficient Two-Stream Network for Isolated Sign Language Recognition Using Accumulative Video MotionCode0
Topic Detection in Continuous Sign Language VideosCode0
ASL-Homework-RGBD Dataset: An annotated dataset of 45 fluent and non-fluent signers performing American Sign Language homeworks—0
One Model is Not Enough: Ensembles for Isolated Sign Language Recognition—0
Continuous Sign Language Recognition via Temporal Super-Resolution Network—0
Spatial Attention-Based 3D Graph Convolutional Neural Network for Sign Language Recognition—0
Improving Signer Independent Sign Language Recognition for Low Resource Languages—0
Greek Sign Language Recognition for the SL-ReDu Learning Platform—0
PeruSIL: A Framework to Build a Continuous Peruvian Sign Language Interpretation Dataset—0
Challenges with Sign Language Datasets for Sign Language Recognition and Translation—0
Keypoint based Sign Language Translation without Glosses—0
Multi-View Spatial-Temporal Network for Continuous Sign Language Recognition—0
A Token-level Contrastive Framework for Sign Language TranslationCode0
Multi-scale temporal network for continuous sign language recognition—0
A Comprehensive Review of Sign Language Recognition: Different Types, Modalities, and Datasets—0
A Transformer-Based Contrastive Learning Approach for Few-Shot Sign Language Recognition—0
Word separation in continuous sign language using isolated signs and post-processing—0
Gesture based Arabic Sign Language Recognition for Impaired People based on Convolution Neural Network—0
Bangla sign digits recognition using depth information—0
Statistical and Spatio-temporal Hand Gesture Features for Sign Language Recognition using the Leap Motion Sensor—0
ASL Video Corpora & Sign Bank: Resources Available through the American Sign Language Linguistic Research Project (ASLLRP)—0
Towards Zero-shot Sign Language Recognition—0
ASL-Skeleton3D and ASL-Phono: Two Novel Datasets for the American Sign Language—0
All You Need In Sign Language Production—0
Sign Language Recognition System using TensorFlow Object Detection API—0
Enhanced dynamic sign language recognition using slowfast networks—0
End-To-End Sign Language Translation via Multitask Learning—0
ASL Trigger Recognition in Mixed Activity/Signing Sequences for RF Sensor-Based User InterfacesCode0
Latent Cognizance: What Machine Really Learns—0
Using Motion History Images with 3D Convolutional Networks in Isolated Sign Language Recognition—0
SignBERT: Pre-Training of Hand-Model-Aware Representation for Sign Language Recognition—0
Multi-Modal Zero-Shot Sign Language Recognition—0
ZS-SLR: Zero-Shot Sign Language Recognition from RGB-D Videos—0
Egyptian Sign Language Recognition Using CNN and LSTM—0
Multi-Scale Local-Temporal Similarity Fusion for Continuous Sign Language Recognition—0
PiSLTRc: Position-informed Sign Language Transformer with Content-aware Convolution—0
Bangla sign language recognition using concatenated BdSL network—0
LSFB-CONT and LSFB-ISOL: Two New Datasets for Vision-Based Sign Language RecognitionCode0
Word-level Sign Language Recognition with Multi-stream Neural Networks Focusing on Local Regions and Skeletal Information—0
Towards data-driven sign language interpreting virtual assistant—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