  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.

Computer Vision and Pattern Recognition