AIBullisharXiv – CS AI · 15h ago6/10
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Hands-On: Segmenting Individual Signs from Continuous Sequences
Researchers have developed a transformer-based architecture for continuous sign language segmentation, using the BIO tagging scheme and HaMeR hand features combined with 3D angles. The method achieves state-of-the-art results on DGS Corpus and surpasses benchmarks on BSLCorpus, with significant implications for automated sign language translation and dataset annotation.