Image analytics using artificial intelligence : pose guided human image generation with deep neural network
Given the widespread problems of gelatinization and texture loss in the current image generation, a pose-guided human image generation model with RFB (Receptive Field Block) and SE (Squeeze-and-Excitation) Module added is proposed. This model uses GAN (Generative Adversarial Network) for training. I...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/150150 |