activity
20182022
most citedQuantitative Survey of the State of the Art in Sign Language Recognition

59 citations · 68 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CL20224 cited

Clean Text and Full-Body Transformer: Microsoft's Submission to the WMT22 Shared Task on Sign Language Translation

Subhadeep Dey, Abhilash Pal, Cyrine Chaabani +1

This paper describes Microsoft's submission to the first shared task on sign language translation at WMT 2022, a public competition tackling sign language to spoken language transl…

eess.AS20215 cited

Dialectal Speech Recognition and Translation of Swiss German Speech to Standard German Text: Microsoft's Submission to SwissText 2021

Yuriy Arabskyy, Aashish Agarwal, Subhadeep Dey +1

This paper describes the winning approach in the Shared Task 3 at SwissText 2021 on Swiss German Speech to Standard German Text, a public competition on dialect recognition and tra…

cs.CV2020

Multi-channel Transformers for Multi-articulatory Sign Language Translation

Necati Cihan Camgoz, Oscar Koller, Simon Hadfield +1

Sign languages use multiple asynchronous information channels (articulators), not just the hands but also the face and body, which computational approaches often ignore. In this pa…

cs.CV202059 cited

Quantitative Survey of the State of the Art in Sign Language Recognition

Oscar Koller

This work presents a meta study covering around 300 published sign language recognition papers with over 400 experimental results. It includes most papers between the start of the…

cs.CV2020

Sign Language Transformers: Joint End-to-end Sign Language Recognition and Translation

Necati Cihan Camgoz, Oscar Koller, Simon Hadfield +1

Prior work on Sign Language Translation has shown that having a mid-level sign gloss representation (effectively recognizing the individual signs) improves the translation performa…

cs.CV2019

Sign Language Recognition, Generation, and Translation: An Interdisciplinary Perspective

Danielle Bragg, Oscar Koller, Mary Bellard +9

Developing successful sign language recognition, generation, and translation systems requires expertise in a wide range of fields, including computer vision, computer graphics, nat…