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 201–250 of 297 papers

TitleStatusHype
Unsupervised Term Discovery for Continuous 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
Using Motion History Images with 3D Convolutional Networks in Isolated Sign Language Recognition—0
Video-based Sign Language Recognition without Temporal Segmentation—0
Visual Methods for Sign Language Recognition: A Modality-Based Review—0
Visual Speech Recognition—0
VSNet: Focusing on the Linguistic Characteristics of Sign Language—0
Word-level Sign Language Recognition with Multi-stream Neural Networks Focusing on Local Regions and Skeletal Information—0
Word separation in continuous sign language using isolated signs and post-processing—0
Zero-Shot Sign Language Recognition: Can Textual Data Uncover Sign Languages?—0
ZS-SLR: Zero-Shot Sign Language Recognition from RGB-D Videos—0
1DCNNTrans: BISINDO Sign Language Interpreters in Improving the Inclusiveness of Public Services—0
3D Face Tracking and Multi-Scale, Spatio-temporal Analysis of Linguistically Significant Facial Expressions and Head Positions in ASL—0
A Chinese Continuous Sign Language Dataset Based on Complex Environments—0
A Comparative Analysis of Techniques and Algorithms for Recognising Sign Language—0
A Comparative Study of Continuous Sign Language Recognition Techniques—0
A Comprehensive Review of Sign Language Recognition: Different Types, Modalities, and Datasets—0
A Dataset for Linguistic Understanding, Visual Evaluation, and Recognition of Sign Languages: The K-RSL—0
Advanced Arabic Alphabet Sign Language Recognition Using Transfer Learning and Transformer Models—0
A Hong Kong Sign Language Corpus Collected from Sign-interpreted TV News—0
All You Need In Sign Language Production—0
American Sign Language fingerspelling recognition in the wild—0
American Sign Language Identification Using Hand Trackpoint Analysis—0
American Sign Language Recognition Using RF Sensing—0
A New Framework for Sign Language Recognition based on 3D Handshape Identification and Linguistic Modeling—0
An Open Web Platform for Rule-Based Speech-to-Sign Translation—0
APALU: A Trainable, Adaptive Activation Function for Deep Learning Networks—0
A platform-independent user-friendly dictionary from Italian to LIS—0
A Sign Language Recognition System with Pepper, Lightweight-Transformer, and LLM—0
ASL Citizen: A Community-Sourced Dataset for Advancing Isolated Sign Language Recognition—0
ASL-Homework-RGBD Dataset: An annotated dataset of 45 fluent and non-fluent signers performing American Sign Language homeworks—0
ASL-Skeleton3D and ASL-Phono: Two Novel Datasets for the American Sign Language—0
ASL Video Corpora & Sign Bank: Resources Available through the American Sign Language Linguistic Research Project (ASLLRP)—0
A Tale of Two Languages: Large-Vocabulary Continuous Sign Language Recognition from Spoken Language Supervision—0
A Transformer-Based Contrastive Learning Approach for Few-Shot Sign Language Recognition—0
A Transformer-Based Multi-Stream Approach for Isolated Iranian Sign Language Recognition—0
A Transformer Model for Boundary Detection in Continuous Sign Language—0
Exploring Attention Mechanisms in Integration of Multi-Modal Information for Sign Language Recognition and Translation—0
A two-way translation system of Chinese sign language based on computer vision—0
Audio-Visual Speech and Gesture Recognition by Sensors of Mobile Devices—0
AUTSL: A Large Scale Multi-modal Turkish Sign Language Dataset and Baseline Methods—0
Bangla sign digits recognition using depth information—0
Bangla sign language recognition using concatenated BdSL network—0
BAUST Lipi: A BdSL Dataset with Deep Learning Based Bangla Sign Language Recognition—0
BdSLW401: Transformer-Based Word-Level Bangla Sign Language Recognition Using Relative Quantization Encoding (RQE)—0
Bengali Sign Language Recognition through Hand Pose Estimation using Multi-Branch Spatial-Temporal Attention Model—0
BEST: BERT Pre-Training for Sign Language Recognition with Coupling Tokenization—0
Beyond Words: AuralLLM and SignMST-C for Precise Sign Language Production and Bidirectional Accessibility—0
Boosting Continuous Sign Language Recognition via Cross Modality Augmentation—0
BosphorusSign22k Sign Language Recognition Dataset—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