mlsanityData to 7 Oct 2026

Sign language segmentation with temporal convolutional networks

arXiv 2011.12986 ↗First posted 25 Nov 2020cs.CVcited by 14

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Abstract (arXiv)

The objective of this work is to determine the location of temporal boundaries between signs in continuous sign language videos. Our approach employs 3D convolutional neural network representations with iterative temporal segment refinement to resolve ambiguities between sign boundary cues. We demonstrate the effectiveness of our approach on the BSLCORPUS, PHOENIX14 and BSL-1K datasets, showing considerable improvement over the prior state of the art and the ability to generalise to new signers, languages and domains.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Nov 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 0; 2023: 1; 2024: 1; 2025: 6; 2026: 3.

14 papers.

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  1. 2021BBC-Oxford British Sign Language Datasetcited by 27
  2. 2023Linguistically Motivated Sign Language Segmentationcited by 11
  3. 2021Sign Segmentation with Changepoint-Modulated Pseudo-Labellingcited by 10
  4. 2025Hands-On: Segmenting Individual Signs from Continuous Sequencescited by 10
  5. 2021Fingerspelling Detection in American Sign Languagecited by 7
  6. 2025Segment, Embed, and Align: A Universal Recipe for Aligning Subtitles to Signingcited by 2
  7. 2026SignSparK: Efficient Multilingual Sign Language Production via Sparse Keyframe Learningcited by 2
  8. 2024An Open-Source American Sign Language Fingerspell Recognition and Semantic Pose Retrieval Interfacecited by 0
  9. 2025iLSU-T: an Open Dataset for Uruguayan Sign Language Translationcited by 0
  10. 2025The TUB Sign Language Corpus Collectioncited by 0
  11. 2025SSL-SLR: Self-Supervised Representation Learning for Sign Language Recognitioncited by 0
  12. 2025MHB: Multimodal Handshape-aware Boundary Detection for Continuous Sign Language Recognitioncited by 0
2 more
  1. 2026SMART: MLLM-guided Temporal Alignment for Unifying Sign Language Recognition and Spottingcited by 0
  2. 2026Machine Translation for Sign Languagescited by 0