SignMatch introduces a prototype‑structured embedding space that learns to match dictionary sign videos with continuous sign language footage based solely on visual similarity of handshape and motion. By mapping isolated dictionary exemplars into this space, the method enables direct, embedding‑based sign matching and can generalise to unseen signs using only dictionary examples. Experiments on ASL‑Citizen, ChaLearn OSLWL, and BOBSL CSLR2 benchmarks show strong cross‑dataset, cross‑task, and cross‑language performance, outperforming prior approaches on American, British, and Spanish sign languages without benchmark‑specific supervision.
By Ryan Wong, Youngjoon Jang, Liliane Momeni, G\"ul Varol, Andrew Zisserman
arXiv:2605. 01720v3 Announce Type: replace-cross Abstract: Existing large-scale sign language resources typically provide supervision only at the level of raw video-text alignment and are often produced in laboratory settings.
By Sen Fang, Hongbin Zhong, Yanxin Zhang, Dimitris N. Metaxas
arXiv:2608. 09045v1 Announce Type: cross Abstract: Recent advances in sign language (SL) research have shown a trend toward unifying multiple sign language understanding (SLU) subtasks, such as isolated sign language recognition (ISLR), continuous sign language recognition (CSLR), and sign language translation (SLT), within a single framework, leading to substantial progress.
By Xiao Liu, Shiwei Gan, Yafeng Yin, Jiaxin Yin, Bowen Guo, Yaqi Sun, Zhiwei Jiang, Lei Xie
arXiv:2606. 19352v1 Announce Type: cross Abstract: Sign languages are expressive visual languages used by Deaf and Hard-of-Hearing (DHH) communities.
By Yiming Ni, Zhi-Qi Cheng, Jiayu Li, Wei Cheng
arXiv:2610.00881v1 Announce Type: new
Abstract: Sign language machine translation has progressed substantially over the past decade, evolving from isolated sign recognition to end-to-end translation...
By Ozge Mercanoglu Sincan, Anton Pelykh, Edward Fish, Harry Walsh, JianHe Low, Karahan Sahin, Oline Ranum, Sobhan Asasi, Steven Emery, Richard Bowden
arXiv:2608. 06407v1 Announce Type: cross Abstract: Automated Sign Language Recognition for under-represented languages remains a largely unsolved problem.
By Lucia Yen Wanchi, Samuel Johnny, Victor Tolulope Olufemi, Emmanuel Aaron, Moise Busogi