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Translating in Style
Nir Chachamovitz and Ilan Doron
Supervised by Elad Richardson
In this project we introduce an implementation of an open-source system for automatically recognizing and translating text in pictures, posters, road signs etc. Unlike in existing projects, we focused on preserving the original text style in order to create visually-pleasing results. In addition, effort was made to maintain and preserve the original background of text containing regions within the images.
The project explores:
Deep models for text detection and recognition: We used an already-trained text detection and recognition networks, and a few more deep models in several steps of the pipeline.
Style transfer and image blending techniques: We used perspective transformation technique and other image blending tools.