An Unpaired Sketch-to-Photo Translation Model

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Deep Learning Unpaired-Sketch-to-Photo-Translation
Overview

Unpaired-Sketch-to-Photo-Translation

#f03c15 We have released our code at https://github.com/rt219/Unsupervised-Sketch-to-Photo-Synthesis

This project is the implementation of Unsupervised Sketch to Photo Synthesis (arxiv: https://arxiv.org/abs/1909.08313).

Photo Generation Examples

This figure shows generated photo images using the proposed model. From left to right: input sketch, generated grayscale photo (shape translation), generated RGB photo (basic colorization), generated RGB photo condition on reference photo (improved colorization), two nearest neighbors of the generated RGB photo. To retrieve the nearest neighbours, we employed an ImageNet pre-trained ResNet18 to extract the deep feature of each image, and computed L2 distance for comparison.

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Sketch Generation Examples

This figure shows generated sketch images using the proposed model.

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Accumulative Results

This figure shows generated grayscale photo images corresponding to accumulative sketches. The last two images of each example are the final outputs. Accumulative sketches are obtained by manipulating images in SVG format.

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Comments
  • Implementation code

    Implementation code

    Hey, First of all, I wanted to congratulate you on the paper. The approach sounds very promising and the presented results look really great. Could you tell me when you are likely to upload the source code of the implementation?

    opened by hvoss-techfak 3
Owner
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GitHub https://arxiv.org/abs/1909.08313
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