Skin Textural Generation via Blue-noise Gabor Filtering based Generative Adversarial Network
| Autor: | Jue Wang, Hui Zhang, Chuan Wang, Wenping Wang, Nenglun Chen |
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| Rok vydání: | 2020 |
| Předmět: |
Computer science
Property (programming) business.industry Deep learning ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020207 software engineering Pattern recognition 02 engineering and technology Noise Gabor filter Colors of noise Face (geometry) 0202 electrical engineering electronic engineering information engineering Image translation 020201 artificial intelligence & image processing Artificial intelligence business Texture synthesis |
| Zdroj: | ACM Multimedia |
| Popis: | Facial skin texture synthesis is a fundamental problem in high-quality facial image generation and enhancement. The key behind is how to effectively synthesize plausible textured noise for the faces. With the development of CNNs and GANs, most works cast the problem as an image to image translation problem. However, these methods lack an explicit mechanism to simulate the facial noise pattern, so that the generated images are of obvious artifacts. To this end, we propose a new facial noise generation method. Specifically, we utilize the property of blue noise and Gabor filter to implicitly guide the asymmetrical sampling for the face region as a guidance map, where non-uniform point sampling is conducted. Thus we propose a novel Blue-Noise Gabor Module to produce a spatial-variant noisy image. Our proposed two-branch framework combined facial identity enhancing with textures details generation to jointly produce a high-quality facial image. Experimental results demonstrate the superiority of our method compared with the state-of-the-art, which enables the generation of high-quality facial texture based on a 2D image only, without the involvement of any 3D models. |
| Databáze: | OpenAIRE |
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