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
BosphorusSign: A Turkish Sign Language Recognition Corpus in Health and Finance Domains—0
Breaking the Barriers: Video Vision Transformers for Word-Level Sign Language Recognition—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
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
Denoising-Contrastive Alignment for Continuous Sign Language Recognition—0
Connecting the Dots: Leveraging Spatio-Temporal Graph Neural Networks for Accurate Bangla Sign Language Recognition—0
Connectionist Temporal Fusion for Sign Language Translation—0
Continuous sign language recognition based on cross-resolution knowledge distillation—0
Continuous Sign Language Recognition Based on Motor attention mechanism and frame-level Self-distillation—0
Continuous sign language recognition from wearable IMUs using deep capsule networks and game theory—0
Continuous Sign Language Recognition System using Deep Learning with MediaPipe Holistic—0
Continuous Sign Language Recognition Through Cross-Modal Alignment of Video and Text Embeddings in a Joint-Latent Space—0
Continuous Sign Language Recognition through a Context-Aware Generative Adversarial Network—0
Continuous Sign Language Recognition Using Intra-inter Gloss Attention—0
Continuous Sign Language Recognition via Temporal Super-Resolution Network—0
Continuous Sign Language Recognition with Adapted Conformer via Unsupervised Pretraining—0
Contour-based Hand Pose Recognition for Sign Language Recognition—0
Convolutional Neural Network Array for Sign Language Recognition using Wearable IMUs—0
CoSign: Exploring Co-occurrence Signals in Skeleton-based Continuous Sign Language Recognition—0
Coupling Natural Language Processing and Animation Synthesis in Portuguese Sign Language Translation—0
Cross-Language Transfer Learning using Visual Information for Automatic Sign Gesture Recognition—0
Deep Hand: How to Train a CNN on 1 Million Hand Images When Your Data Is Continuous and Weakly Labelled—0
Deep Learning Recognition for Arabic Alphabet Sign Language RGB Dataset—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
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
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
Enhancing Mathematics Learning for Hard-of-Hearing Students Through Real-Time Palestinian Sign Language Recognition: A New Dataset—0
Enhancing Sequential Model Performance with Squared Sigmoid TanH (SST) Activation Under Data Constraints—0
Evaluating the Immediate Applicability of Pose Estimation for Sign Language Recognition—0
Evaluation of Deep Learning based Pose Estimation for Sign Language Recognition—0
Evaluation of Manual and Non-manual Components for Sign Language Recognition—0
EvSign: Sign Language Recognition and Translation with Streaming Events—0
Exploiting the Logits: Joint Sign Language Recognition and Spell-Correction—0
Extension of hidden markov model for recognizing large vocabulary of sign language—0
Extensions of the Sign Language Recognition and Translation Corpus RWTH-PHOENIX-Weather—0
Facial Expression Phoenix (FePh): An Annotated Sequenced Dataset for Facial and Emotion-Specified Expressions in Sign Language—0
FineHand: Learning Hand Shapes for American Sign Language Recognition—0
Show:102550
← PrevPage 6 of 6Next →

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