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arXiv Computer Vision By Fidel Omar Tito Cruz, Angie Sanchez Marquina, Summy Farfan, Gissella Bejarano

SignRR: Retrieve and Refine Real Motion for Sign Language Production

Read the original on arXiv Computer Vision →

SignRR is a new sign language production framework that combines retrieval of real sign motion segments with a learned refinement step to produce globally coherent signing sequences. It starts from a dictionary of authentic sign segments and refines them using a part-aware Residual VQ‑VAE, preserving fine hand articulation while handling temporal length differences in latent space. Experiments on PHOENIX14T and CSL‑Daily demonstrate state‑of‑the‑art back‑translation performance and competitive pose quality.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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