角超分辨率分割图像的视图合成方法

Dong-Myung Kim, Hyun-Soo Kang, Jae-Won Suh
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引用次数: 0

摘要

近年来,随着深度学习技术的发展,各种基于深度学习的视图合成技术被提出。然而,随着网络性能的提高和变得更加复杂,在处理高分辨率图像时出现内存短缺。针对角度超分辨问题,提出了一种分割图像的视图合成方法。我们的方法使用有限的内存合成高分辨率图像。该算法根据不同的图像分割方法来处理高效的图像合成方法,实验结果表明哪一种方法的合成效果更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
View Synthesis Method with Partitioned Image for Angular Super-Resolution
Recently, with the development of deep learning technology, various view synthesis techniques based on deep learning have been proposed. However, as network performance improves and becomes more complex, the memory shortages occur when processing high-resolution images. In this paper, we propose view synthesis method with partitioned image for angular super-resolution. Our method synthesizes high resolution images using limited memory. The proposed algorithm deals with efficient image compositing methods according to various image partition methods, and the experimental results show which method has better performance.
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