SOURCE-LINKED INTELLIGENCE
SignSeek: Learning Transferable Representations for Sign Dictionary Retrieval
Sign language dictionaries are essential resources for sign language learners, yet automatically retrieving a sign from a dictionary, given only a query video, remains a challenging problem due to the natural variability between signers. Existing sign representation learning methods are built for closed-set recognition, producing embeddings that do not generalise to the open-set, signer-independent setting that retrieval demands. \textbf{SignSeek} closes this gap by contrastively learning sign representations with saliency-guided articulator masking. A contrastive objective aligns same-gloss s
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-03T11:31:47.000Z
First collected: 2026-09-21T04:51:57.792Z. This is not the publication date.