Results 11 to 20 of about 6,175,859 (338)
Two-Stream Network for Sign Language Recognition and Translation [PDF]
Neural Information Processing Systems, 2022 Sign languages are visual languages using manual articulations and non-manual elements to convey information. For sign language recognition and translation, the majority of existing approaches directly encode RGB videos into hidden representations.
Yutong Chen +5 more
semanticscholar +1 more source
Improving Sign Language Translation with Monolingual Data by Sign Back-Translation [PDF]
Computer Vision and Pattern Recognition, 2021 Despite existing pioneering works on sign language translation (SLT), there is a non-trivial obstacle, i.e., the limited quantity of parallel sign-text data.
Hao Zhou +4 more
semanticscholar +1 more source
Sign Language Transformers: Joint End-to-End Sign Language Recognition and Translation [PDF]
Computer Vision and Pattern Recognition, 2020 Prior work on Sign Language Translation has shown that having a mid-level sign gloss representation (effectively recognizing the individual signs) improves the translation performance drastically.
Necati Cihan Camgöz +3 more
semanticscholar +1 more source
Skeleton Aware Multi-modal Sign Language Recognition [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2021 Sign language is commonly used by deaf or speech impaired people to communicate but requires significant effort to master. Sign Language Recognition (SLR) aims to bridge the gap between sign language users and others by recognizing signs from given ...
Songyao Jiang +5 more
semanticscholar +1 more source
Visual Alignment Constraint for Continuous Sign Language Recognition [PDF]
IEEE International Conference on Computer Vision, 2021 Vision-based Continuous Sign Language Recognition (CSLR) aims to recognize unsegmented signs from image streams. Overfitting is one of the most critical problems in CSLR training, and previous works show that the iterative training scheme can partially ...
Yuecong Min +3 more
semanticscholar +1 more source
Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison [PDF]
IEEE Workshop/Winter Conference on Applications of Computer Vision, 2019 Vision-based sign language recognition aims at helping the deaf people to communicate with others. However, most existing sign language datasets are limited to a small number of words.
Dongxu Li +3 more
semanticscholar +1 more source
SAL: Sign Agnostic Learning of Shapes From Raw Data [PDF]
Computer Vision and Pattern Recognition, 2019 Recently, neural networks have been used as implicit representations for surface reconstruction, modelling, learning, and generation. So far, training neural networks to be implicit representations of surfaces required training data sampled from a ground-
Matan Atzmon, Y. Lipman
semanticscholar +1 more source
Signing at Scale: Learning to Co-Articulate Signs for Large-Scale Photo-Realistic Sign Language Production [PDF]
Computer Vision and Pattern Recognition, 2022 Sign languages are visual languages, with vocabularies as rich as their spoken language counterparts. However, current deep-learning based Sign Language Production (SLP) models produce under-articulated skeleton pose sequences from constrained ...
Ben Saunders, N. C. Camgoz, R. Bowden
semanticscholar +1 more source
How2Sign: A Large-scale Multimodal Dataset for Continuous American Sign Language [PDF]
Computer Vision and Pattern Recognition, 2020 One of the factors that have hindered progress in the areas of sign language recognition, translation, and production is the absence of large annotated datasets. Towards this end, we introduce How2Sign, a multimodal and multiview continuous American Sign
A. Duarte +6 more
semanticscholar +1 more source
Sign Language Recognition, Generation, and Translation: An Interdisciplinary Perspective [PDF]
International ACM SIGACCESS Conference on Computers and Accessibility, 2019 Developing successful sign language recognition, generation, and translation systems requires expertise in a wide range of fields, including computer vision, computer graphics, natural language processing, human-computer interaction, linguistics, and ...
Danielle Bragg +11 more
semanticscholar +1 more source