We're releasing a state-of-the-art multilingual and multi-domain neural machine translation model specialised for biomedical data that enables translation into English from five languages (French, German, Italian, Spanish and Korean).
A new platform based on deep-learning approaches to handwritten-text recognition and information extraction enables data from century-old documents to be parsed and analysed, making it possible to explore epidemics and the evolution of populations over time.
Latest release of the popular synthetic image dataset for training and testing. New features include increased photorealism, stereo cameras and additional ground truth.
This article introduces our recent arxiv preprint on further understanding human actions out of context thanks to the newly introduced Mimetics dataset.
EMNLP 2019 was in Hong Kong and received a record-breaking number of submissions, but here is a very biased selection of what we liked from the things we saw.
Evaluating our method on public datasets, we show that it can successfully solve challenging situations in dynamic environments which cause state-of-the-art baseline VSLAM algorithms to fail and that it maintains performance on static scenes.
A new double depth-map representation of the human shape allows to recover 3D details from a single image. Using 2 depth maps (visible and hidden) makes representations more efficient and easier to handle.
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