Generating large scale images using GANs

Mohamed Mohsen; Mohamed Moustafa

doi:10.1117/12.2540489

14 August 2019 Generating large scale images using GANs

Mohamed Mohsen, Mohamed Moustafa

Proceedings Volume 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019); 111790N (2019) https://doi.org/10.1117/12.2540489
Event: Eleventh International Conference on Digital Image Processing (ICDIP 2019), 2019, Guangzhou, China

Abstract

Generative Adversarial Networks (GANs) have been used for the task of image generation and has achieved impressive results. There is always a challenge to train networks that generate large scale images since they tend to be huge and training needs a lot of data. In this work, we tackle this problem by dividing it into two smaller parts. We first generate small scale images using GANs then use a super resolution network to enlarge the generated images resulting in large scale images. Using a super resolution network helps in adding more details to the image which results in a better-quality image. This technique has been tested with a small amount of data to generate 128x128 pixel images and obtained better inception scores over the baseline GAN.

Citation Download Citation

Mohamed Mohsen and Mohamed Moustafa "Generating large scale images using GANs", Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111790N (14 August 2019); https://doi.org/10.1117/12.2540489

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