A method learns synthetic-to-real parameter corrections from source languages and transfers them to target languages without any real target data, improving HTR across five languages and six models.
Learning to diversify for single do- main generalization.2021 IEEE/CVF International Confer- ence on Computer Vision (ICCV), 2021
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Zero-Shot Synthetic-to-Real Handwritten Text Recognition via Task Analogies
A method learns synthetic-to-real parameter corrections from source languages and transfers them to target languages without any real target data, improving HTR across five languages and six models.