ReSCUE: Re-translation with Sentence Commitment for Unsegmented Long-Form Simultaneous Sign Language Translation

ReSCUE is a unified framework for simultaneous sign language translation on unsegmented long‑form videos, aligning training and inference with realistic streaming conditions. It incorporates inference‑aware training to manage partial inputs, non‑signing pauses, and multi‑sentence contexts; stabilized re‑translation for low‑latency, revisable predictions with reduced output flicker; and a sentence commitment mechanism for online segmentation and memory management. Experiments show ReSCUE achieves lower latency and superior translation quality in low‑latency settings, approaching oracle offline systems on long‑form datasets while operating at substantially lower latency.

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• computer-vision
• benchmarks