{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/fingerspelling-posenet-enhancing","title":"Fingerspelling PoseNet: Enhancing Fingerspelling Translation with Pose-Based Transformer Models","arxiv_id":"2311.12128","date":"2023-11-20","proceeding":null,"authors":["Pooya Fayyazsanavi","Negar Nejatishahidin","Jana Kosecka"],"abstract":"We address the task of American Sign Language fingerspelling translation using videos in the wild. We exploit advances in more accurate hand pose estimation and propose a novel architecture that leverages the transformer based encoder-decoder model enabling seamless contextual word translation. The translation model is augmented by a novel loss term that accurately predicts the length of the finger-spelled word, benefiting both training and inference. We also propose a novel two-stage inference approach that re-ranks the hypotheses using the language model capabilities of the decoder. Through extensive experiments, we demonstrate that our proposed method outperforms the state-of-the-art models on ChicagoFSWild and ChicagoFSWild+ achieving more than 10% relative improvement in performance. Our findings highlight the effectiveness of our approach and its potential to advance fingerspelling recognition in sign language translation. Code is also available at https://github.com/pooyafayyaz/Fingerspelling-PoseNet.","url_abs":"https://arxiv.org/abs/2311.12128v1","url_pdf":"https://arxiv.org/pdf/2311.12128v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"fingerspelling-posenet-enhancing","repo_url":"https://github.com/pooyafayyaz/fingerspelling-posenet","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"decoder","task_name":"Decoder"},{"task_slug":"hand-pose-estimation","task_name":"Hand Pose Estimation"},{"task_slug":"language-modeling","task_name":"Language Modeling"},{"task_slug":"language-modelling","task_name":"Language Modelling"},{"task_slug":"pose-estimation","task_name":"Pose Estimation"},{"task_slug":"sign-language-translation","task_name":"Sign Language Translation"},{"task_slug":"translation","task_name":"Translation"},{"task_slug":"word-translation","task_name":"Word Translation"}],"methods":[{"method_slug":null,"method_name":"American"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}