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Mononizing Binocular Videos
arXiv - CS - Graphics Pub Date : 2020-09-03 , DOI: arxiv-2009.01424
Wenbo Hu, Menghan Xia, Chi-Wing Fu, and Tien-Tsin Wong

This paper presents the idea ofmono-nizingbinocular videos and a frame-work to effectively realize it. Mono-nize means we purposely convert abinocular video into a regular monocular video with the stereo informationimplicitly encoded in a visual but nearly-imperceptible form. Hence, wecan impartially distribute and show the mononized video as an ordinarymonocular video. Unlike ordinary monocular videos, we can restore from itthe original binocular video and show it on a stereoscopic display. To start,we formulate an encoding-and-decoding framework with the pyramidal de-formable fusion module to exploit long-range correspondences between theleft and right views, a quantization layer to suppress the restoring artifacts,and the compression noise simulation module to resist the compressionnoise introduced by modern video codecs. Our framework is self-supervised,as we articulate our objective function with loss terms defined on the input:a monocular term for creating the mononized video, an invertibility termfor restoring the original video, and a temporal term for frame-to-framecoherence. Further, we conducted extensive experiments to evaluate ourgenerated mononized videos and restored binocular videos for diverse typesof images and 3D movies. Quantitative results on both standard metrics anduser perception studies show the effectiveness of our method.

中文翻译:

单目双目视频

本文提出了单目双目视频的思想和有效实现它的框架。Mono-nize 意味着我们有意将双目视频转换为常规单目视频,其中立体信息以视觉但几乎无法察觉的形式隐式编码。因此,我们可以公正地分发和展示单眼视频作为普通单眼视频。与普通的单目视频不同,我们可以从中还原出原始的双目视频,并在立体显示器上显示出来。首先,我们制定了一个编码和解码框架,其中包含金字塔形可变形融合模块以利用左视图和右视图之间的长距离对应关系、一个量化层来抑制恢复伪影,以及一个压缩噪声模拟模块来抵抗现代视频编解码器引入的压缩噪声。我们的框架是自监督的,因为我们用输入上定义的损失项来阐明我们的目标函数:用于创建单一化视频的单目项、用于恢复原始视频的可逆项以及用于帧到帧相干性的时间项。此外,我们进行了广泛的实验来评估我们生成的单目视频和为各种类型的图像和 3D 电影恢复的双目视频。标准指标和用户感知研究的定量结果表明了我们方法的有效性。我们进行了广泛的实验来评估我们生成的单一化视频和为各种类型的图像和 3D 电影恢复的双目视频。标准指标和用户感知研究的定量结果表明了我们方法的有效性。我们进行了广泛的实验来评估我们生成的单一化视频和为各种类型的图像和 3D 电影恢复的双目视频。标准指标和用户感知研究的定量结果表明了我们方法的有效性。
更新日期:2020-09-04
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