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Uncanny Rd. – Drawing tool to interactively synthesise street images
Uncanny Rd. is a drawing tool that allows users to interactively synthesise street images with the help of Generative Adversarial Networks (GANs). The project was created as a collaboration between Anastasis Germanidis and Cristobal Valenzuela to explore new kinds of human-machine collaboration that deep learning can enable.
The project and uses two AI research papers published last year as a starting point (Image-to-Image Translation Using Conditional Adversarial Networks by Isola et al. and High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs by Wang et al.) Users are asked to interact with a semantic colormap of a scene, where each color represents a different kind of object label (e.g. road, building, vegetation, etc.). The neural network model was trained using adversarial learning on the Cityscapes dataset, which contains street images from a number of German cities.
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