GARD is a context-aware autoregressive diffusion model for gloss-wise sign language production using inter-gloss transition guidance and global motion harmonizer, claiming superior linguistic accuracy and motion similarity on Phoenix-T and CSL-Daily datasets.
arXiv preprint arXiv:2308.16082 (2023)
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A survey indexes 120 sign-language datasets from 35 languages, identifies modality, annotation, and bias issues, and proposes a standardized 24-field datasheet with an open repository.
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Sign-Language Datasets at Scale: A Comprehensive Survey on Resources, Benchmarks, and Annotation Standards
A survey indexes 120 sign-language datasets from 35 languages, identifies modality, annotation, and bias issues, and proposes a standardized 24-field datasheet with an open repository.