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Challenges with Sign Language Datasets for Sign Language Recognition and Translation.

, , , , , и . LREC, стр. 2478-2487. European Language Resources Association, (2022)

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Leveraging Frozen Pretrained Written Language Models for Neural Sign Language Translation., и . Inf., 13 (5): 220 (2022)Isolated Sign Recognition From RGB Video Using Pose Flow and Self-Attention., , и . CVPR Workshops, стр. 3441-3450. Computer Vision Foundation / IEEE, (2021)Predicting Errors and Failures in Human-Robot Interaction from Multi-Modal Temporal Data., , и . ICMI, стр. 671-676. ACM, (2024)Querying A Sign Language Dictionary with Videos Using Dense Vector Search., и . ICASSP Workshops, стр. 1-5. IEEE, (2023)Machine translation from signed to spoken languages: state of the art and challenges., , , и . Univers. Access Inf. Soc., 23 (3): 1305-1331 (августа 2024)From Scarcity to Understanding: Transfer Learning for the Extremely Low Resource Irish Sign Language., , , , , , и . ICCV (Workshops), стр. 2000-2009. IEEE, (2023)Challenges with Sign Language Datasets for Sign Language Recognition and Translation., , , , , и . LREC, стр. 2478-2487. European Language Resources Association, (2022)SignON - a Co-creative Machine Translation for Sign and Spoken Languages (end-of-project results, contributions and lessons learned)., , , , , , , , , и 16 other автор(ы). EAMT (2), стр. 49-50. European Association for Machine Translation (EAMT), (2024)Towards the extraction of robust sign embeddings for low resource sign language recognition., , , , и . CoRR, (2023)SignON: Sign Language Translation. Progress and challenges., , , , , , , , , и 13 other автор(ы). EAMT, стр. 501-502. European Association for Machine Translation, (2023)