Generation of stereo images based on a view synthesis network

Yuan Mau Lo, Chin Chen Chang*, Der Lor Way, Zen-Chung Shih


研究成果: Article同行評審

1 引文 斯高帕斯(Scopus)


The conventional warping method only considers translations of pixels to generate stereo images. In this paper, we propose a model that can generate stereo images from a single image, considering both translation as well as rotation of objects in the image. We modified the appearance flow network to make it more general and suitable for our model. We also used a reference image to improve the inpainting method. The quality of images resulting from our model is better than that of images generated using conventional warping. Our model also better retained the structure of objects in the input image. In addition, our model does not limit the size of the input image. Most importantly, because our model considers the rotation of objects, the resulting images appear more stereoscopic when viewed with a device.

原文American English
期刊Applied Sciences (Switzerland)
出版狀態Published - 1 5月 2020


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