ManiGAN: Text-guided image manipulation
The goal of our paper is to semantically edit parts of an image matching a given text that describes desired attributes (e.g., texture, colour, and background), while preserving other contents that are irrelevant to the text. To achieve this, we propose a novel generative adversarial network (ManiGA...
| Main Authors: | , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
IEEE
2020
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