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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 17 of 17 1 BBC-Oxford British Sign Language Dataset Albanie, Samuel; Varol, Gül; Momeni, Liliane... In: https://hal.archives-ouvertes.fr/hal-03516444 ; 2022 (2022) BASE Show details 2 Sign Language Video Retrieval with Free-Form Textual Queries ... Duarte, Amanda; Albanie, Samuel; Giró-i-Nieto, Xavier. - : arXiv, 2022 BASE Show details 3 A 23 MW data centre is all you need ... Albanie, Samuel; Campbell, Dylan; Henriques, João F.. - : arXiv, 2022 BASE Show details 4 Aligning Subtitles in Sign Language Videos Bull, Hannah; Afouras, Triantafyllos; Varol, Gül... In: International Conference on Computer Vision (ICCV) ; https://hal.archives-ouvertes.fr/hal-03515983 ; International Conference on Computer Vision (ICCV), Oct 2021, Montreal, Canada (2021) BASE Show details 5 Sign Segmentation with Changepoint-Modulated Pseudo-Labelling Varol, Gül; Renz, Katrin; Stache, Nicolaj C.... In: 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) ; https://hal.archives-ouvertes.fr/hal-03513415 ; 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Jun 2021, Nashville, TN, United States. ⟨10.1109/CVPRW53098.2021.00379⟩ (2021) BASE Show details 6 Read and Attend: Temporal Localisation in Sign Language Videos Varol, Gül; Momeni, Liliane; Albanie, Samuel... In: 2021 IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2021) ; https://hal.archives-ouvertes.fr/hal-03513396 ; 2021 IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2021), Jun 2021, Nashville, TN, United States. ⟨10.1109/CVPR46437.2021.01658⟩ (2021) BASE Show details 7 Sign language segmentation with temporal convolutional networks Varol, Gül; Renz, Katrin; Stache, Nicolaj C.... In: 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ; https://hal.archives-ouvertes.fr/hal-03513405 ; 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Jun 2021, Toronto, ON, Canada. ⟨10.1109/ICASSP39728.2021.9413817⟩ (2021) BASE Show details 8 Read and Attend: Temporal Localisation in Sign Language Videos ... Varol, Gül; Momeni, Liliane; Albanie, Samuel. - : arXiv, 2021 BASE Show details 9 Sign Segmentation with Changepoint-Modulated Pseudo-Labelling ... Renz, Katrin; Stache, Nicolaj C.; Fox, Neil. - : arXiv, 2021 BASE Show details 10 Aligning Subtitles in Sign Language Videos ... Bull, Hannah; Afouras, Triantafyllos; Varol, Gül. - : arXiv, 2021 BASE Show details 11 BBC-Oxford British Sign Language Dataset ... Albanie, Samuel; Varol, Gül; Momeni, Liliane. - : arXiv, 2021 BASE Show details 12 BSL-1K: Scaling up co-articulated sign language recognition using mouthing cues Varol, Gül; Albanie, Samuel; Momeni, Liliane; Afouras, Triantafyllos; Chung, Joon Son; Fox, Neil; Zisserman, Andrew In: European Conference on Computer Vision (ECCV) 2020 ; https://hal.archives-ouvertes.fr/hal-03516489 ; European Conference on Computer Vision (ECCV) 2020, Aug 2020, Glasgow, United Kingdom. ⟨10.1007/978-3-030-58621-8_3⟩ (2020) Abstract: International audience ; Recent progress in fine-grained gesture and action classification, and machine translation, point to the possibility of automated sign language recognition becoming a reality. A key stumbling block in making progress towards this goal is a lack of appropriate training data, stemming from the high complexity of sign annotation and a limited supply of qualified annotators. In this work, we introduce a new scalable approach to data collection for sign recognition in continuous videos. We make use of weakly-aligned subtitles for broadcast footage together with a keyword spotting method to automatically localise sign-instances for a vocabulary of 1,000 signs in 1,000 hours of video. We make the following contributions: (1) We show how to use mouthing cues from signers to obtain high-quality annotations from video data - the result is the BSL-1K dataset, a collection of British Sign Language (BSL) signs of unprecedented scale; (2) We show that we can use BSL-1K to train strong sign recognition models for co-articulated signs in BSL and that these models additionally form excellent pretraining for other sign languages and benchmarks - we exceed the state of the art on both the MSASL and WLASL benchmarks. Finally, (3) we propose new large-scale evaluation sets for the tasks of sign recognition and sign spotting and provide baselines which we hope will serve to stimulate research in this area. Keyword: [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] URL: https://doi.org/10.1007/978-3-030-58621-8_3 https://hal.archives-ouvertes.fr/hal-03516489 BASE Hide details 13 Watch, read and lookup: learning to spot signs from multiple supervisors Varol, Gül; Momeni, Liliane; Albanie, Samuel... In: Asian Conference on Computer Vision (ACCV) 2020 ; https://hal.archives-ouvertes.fr/hal-03516457 ; Asian Conference on Computer Vision (ACCV) 2020, Nov 2020, Kyoto, Japan. ⟨10.1007/978-3-030-69544-6_18⟩ (2020) BASE Show details 14 Watch, read and lookup: learning to spot signs from multiple supervisors ... Momeni, Liliane; Varol, Gül; Albanie, Samuel. - : arXiv, 2020 BASE Show details 15 Sign language segmentation with temporal convolutional networks ... Renz, Katrin; Stache, Nicolaj C.; Albanie, Samuel. - : arXiv, 2020 BASE Show details 16 BSL-1K: Scaling up co-articulated sign language recognition using mouthing cues ... Albanie, Samuel; Varol, Gül; Momeni, Liliane. - : arXiv, 2020 BASE Show details 17 Disentangled Speech Embeddings using Cross-modal Self-supervision ... Nagrani, Arsha; Chung, Joon Son; Albanie, Samuel. - : arXiv, 2020 BASE Show details

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