SAGE uses a frozen sign-segmentation model to turn sign videos into about half as many visual tokens as prior methods, then aligns those tokens with a language model to reach BLEU-4 of 24.10 on PHOENIX14T.
Hands-on: Segmenting individual signs from continuous sequences
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SAGE: Segment-Aware Gloss-Free Encoding for Token-Efficient Sign Language Translation
SAGE uses a frozen sign-segmentation model to turn sign videos into about half as many visual tokens as prior methods, then aligns those tokens with a language model to reach BLEU-4 of 24.10 on PHOENIX14T.