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Sign Language Recognition On Rwth Phoenix 1

Metrics

Word Error Rate (WER)

Results

Performance results of various models on this benchmark

Model Name
Word Error Rate (WER)
Paper TitleRepository
SlowFastSign18.7SlowFast Network for Continuous Sign Language Recognition-
CrossModal24.3Continuous Sign Language Recognition Through Cross-Modal Alignment of Video and Text Embeddings in a Joint-Latent Space-
WRNN + LET20.73Multimodal Locally Enhanced Transformer for Continuous Sign Language Recognition-
MMTLB22.45A Simple Multi-Modality Transfer Learning Baseline for Sign Language Translation-
MSKA-SLR20.5Multi-Stream Keypoint Attention Network for Sign Language Recognition and Translation-
STMC21.0Spatial-Temporal Multi-Cue Network for Continuous Sign Language Recognition-
SignBT23.9Improving Sign Language Translation with Monolingual Data by Sign Back-Translation-
SMKD22.4Self-Mutual Distillation Learning for Continuous Sign Language Recognition
Stochastic CSLR26.1Stochastic Fine-grained Labeling of Multi-state Sign Glosses for Continuous Sign Language Recognition
SignBERT+19.9SignBERT+: Hand-model-aware Self-supervised Pre-training for Sign Language Understanding-
TwoStream-SLR19.3Two-Stream Network for Sign Language Recognition and Translation-
TCNet19.4TCNet: Continuous Sign Language Recognition from Trajectories and Correlated Regions-
C2SLR20.4C2SLR: Consistency-Enhanced Continuous Sign Language Recognition
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Sign Language Recognition On Rwth Phoenix 1 | SOTA | HyperAI