Paint-your-mind II: stylistic image creation by concept
This report presents a novel approach to generate stylistic paintings from segmentation maps. The proposed method utilizes various image-to-image translation techniques, including artistic style transfer and image enhancement, to generate visually appealing and diverse paintings. The results of the...
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2023
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sg-ntu-dr.10356-1661722023-04-28T15:39:19Z Paint-your-mind II: stylistic image creation by concept Wang, Anyi Cham Tat Jen School of Computer Science and Engineering ASTJCham@ntu.edu.sg Engineering::Computer science and engineering This report presents a novel approach to generate stylistic paintings from segmentation maps. The proposed method utilizes various image-to-image translation techniques, including artistic style transfer and image enhancement, to generate visually appealing and diverse paintings. The results of the experiments show that the proposed method is able to generate paintings that are structurally similar to the input semantic maps, while also incorporating the desired style. A web platform is also developed as part of this project to enable such computer vision techniques to be accessible to the masses in an interactive way. This research has the potential to be applied in a variety of fields such as computer graphics, virtual reality, digital art, or creating convincing prototypes for these tasks. Bachelor of Science in Data Science and Artificial Intelligence 2023-04-24T02:28:44Z 2023-04-24T02:28:44Z 2023 Final Year Project (FYP) Wang, A. (2023). Paint-your-mind II: stylistic image creation by concept. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166172 https://hdl.handle.net/10356/166172 en SCSE22-0283 application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering Wang, Anyi Paint-your-mind II: stylistic image creation by concept |
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This report presents a novel approach to generate stylistic paintings from segmentation maps. The proposed method utilizes various image-to-image translation techniques, including artistic style transfer and image enhancement, to generate visually appealing and diverse paintings. The results of the experiments show that the proposed method is able to generate paintings that are structurally similar to the input semantic maps, while also incorporating the desired style. A web platform is also developed as part of this project to enable such computer vision techniques to be accessible to the masses in an interactive way. This research has the potential to be applied in a variety of fields such as computer graphics, virtual reality, digital art, or creating convincing prototypes for these tasks. |
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Cham Tat Jen |
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Cham Tat Jen Wang, Anyi |
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Final Year Project |
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Wang, Anyi |
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Wang, Anyi |
title |
Paint-your-mind II: stylistic image creation by concept |
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Paint-your-mind II: stylistic image creation by concept |
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Paint-your-mind II: stylistic image creation by concept |
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Paint-your-mind II: stylistic image creation by concept |
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Paint-your-mind II: stylistic image creation by concept |
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paint-your-mind ii: stylistic image creation by concept |
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Nanyang Technological University |
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2023 |
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https://hdl.handle.net/10356/166172 |
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