arXiv AI

SignVerse-2M: A Two-Million-Clip Pose-Native Universe of 55+ Sign Languages

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.

arXiv Machine Learning
Jun 11

Corpus Augmentation for Sign Language Translation via LLM-Guided Video Stitching

arXiv:2606. 11925v1 Announce Type: cross Abstract: Sign language translation (SLT) converts sign language video into spoken language text and holds significant promise for improving accessibility and enabling communication between signing and non-signing communities.

By Zsolt Robotka, \'Ad\'am R\'ak, Jalal Al-Afandi, Andr\'as Horv\'ath, Gy\"orgy Cserey
arXiv AI
Jul 7

ViPo-MLLM: Visual-Pose Multimodal LLM for Gloss-Free Sign Language Translation

arXiv:2607. 03657v1 Announce Type: cross Abstract: Gloss-free Sign Language Translation (SLT) translates sign language videos into spoken-language sentences without gloss annotations, avoiding costly labeling but requiring fine-grained modeling of hands, body, and facial cues.

By Ahmed Abul Hasanaath, Bicheng Xu, Mir Rayat Imtiaz Hossain, Leonid Sigal, Hamzah Luqman
arXiv AI
Jun 6

Tamaththul3D: High-Fidelity 3D Saudi Sign Language Avatars from Monocular Video

arXiv:2605. 05367v2 Announce Type: replace-cross Abstract: Existing 3D sign language avatar reconstruction methods are developed and evaluated exclusively on Western sign languages, and no 3D parametric annotations exist for any Arabic Sign Language dataset, a gap that blocks the development of avatar-based accessibility applications for the Arab Deaf community.

By Eyad Alghamdi, Sattam Altuuaim, Obay Ghulam, Abdulrahman Qutah, Yousef Basoodan
arXiv AI
Aug 11

Bridging the Gap Between Semantics and Reconstruction:Unifying Sign Language Translation and Production

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