Stuff segmentation and non-photorealistic rendering with generative adversarial networks
Generative Adversarial Networks (GANs) have shown impressive results in a variety of image generation tasks in recent years, including rendering photorealistic images with artistic styles. However, current work in transforming images have mostly focused on either transforming the whole image, or on...
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| 格式: | Thesis-Master by Research |
| 語言: | English |
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Nanyang Technological University
2020
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/137213 |
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