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Sign Language Transformers: Joint End-to-End Sign Language Recognition and Translation.

, , , and . CVPR, page 10020-10030. Computer Vision Foundation / IEEE, (2020)

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Deep Sign: Enabling Robust Statistical Continuous Sign Language Recognition via Hybrid CNN-HMMs., , , and . Int. J. Comput. Vis., 126 (12): 1311-1325 (2018)MS-ASL: A Large-Scale Data Set and Benchmark for Understanding American Sign Language., and . CoRR, (2018)First WMT Shared Task on Sign Language Translation (WMT-SLT22)., , , , , , , , , and 10 other author(s). EAMT, page 507-508. European Association for Machine Translation, (2023)MS-ASL: A Large-Scale Data Set and Benchmark for Understanding American Sign Language., and . BMVC, page 100. BMVA Press, (2019)The FATE Landscape of Sign Language AI Datasets: An Interdisciplinary Perspective., , , , , , , , and . ACM Trans. Access. Comput., 14 (2): 7:1-7:45 (2021)Quantitative Survey of the State of the Art in Sign Language Recognition.. CoRR, (2020)Towards large vocabulary continuous sign language recognition: from artificial to real-life tasks.. RWTH Aachen University, Germany, (2020)Improving Continuous Sign Language Recognition: Speech Recognition Techniques and System Design., , , , and . SLPAT, page 41-46. Association for Computational Linguistics, (2013)RWTH-PHOENIX-Weather: A Large Vocabulary Sign Language Recognition and Translation Corpus., , , , , , and . LREC, page 3785-3789. European Language Resources Association (ELRA), (2012)Multi-channel Transformers for Multi-articulatory Sign Language Translation., , , and . ECCV Workshops (4), volume 12538 of Lecture Notes in Computer Science, page 301-319. Springer, (2020)