StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks on ShortScience.org

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StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
Zhang, Han and Xu, Tao and Li, Hongsheng and Zhang, Shaoting and Huang, Xiaolei and Wang, Xiaogang and Metaxas, Dimitris N.
arXiv e-Print archive - 2016 via Local Bibsonomy
Keywords: dblp

Summaries/Notes 2

[link] Summary by Kirill Pevzner 7 years ago

Problem
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Text to image


Contributions
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* Images are more photo realistic and higher resolution then previous methods
* Stacked generative model


Approach
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2 stage process:
1. Text-to-image: generates low resolution image with primitive shape and color.
2. low-to-hi-res: using low res image and text, generates hi res image. adding details and sharpening the edges.

https://pbs.twimg.com/media/Cziw6bfWgAAh3Yg.jpg


Datasets
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* CUB - Birds
* Oxford-102 - Flowers


Results
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https://cdn-images-1.medium.com/max/1012/1*sIphVx4tqaXJxtnZNt3JWA.png


Criticism/ Questions
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* Is it possible the resulting images are replicas of images in the original dataset? To what extent does the model "hallucinate" new images?

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