基于可变形卷积的人工智能立体视图到多视图生成

Wei Hong, J. Yang
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引用次数: 0

摘要

三维(3D)电影是电影工业的主要趋势。在目前的立体视觉中,观众需要佩戴3D眼镜来感知3D可视化。立体电影只有左右视图,无法直接用肉眼显示。为了直接支持需要多视图的裸眼3D显示,我们提出了一种基于深度学习的立体到多视图转换系统,该系统使用可变形卷积来合成额外的虚拟视图。对于沉浸式3D多媒体服务,我们希望能够在不需要深度估计和基于深度图像的渲染功能的情况下,在不戴3D眼镜的情况下提高用户3D体验的质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AI-based Stereoview to Multiview Generation by Using Deformable Convolution
Three dimension (3D) movies are the main trend in the film industry. In the current stereoview, the audiences require wearing 3D glasses to perceive 3D visualization. The 3D movies with stereoview with only left and right views, which cannot be directly displayed in the naked-eyes 3D displays. To directly support naked-eyes 3D displays, which require multiple views, we propose a deep learning based stereo to multiview conversion system by using the deformable convolution to synthesize additional virtual views. For immersive 3D multimedia services, we hope we can improve the quality of user 3D experiences without wearing 3D glasses without the needs of depth estimation and depth image based rendering functions.
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