论文标题
带有多层图像的单视图合成
Single-View View Synthesis with Multiplane Images
论文作者
论文摘要
在View合成中，最近的一项工作使用深度学习来生成多个或多个输入图像在已知角度的两个或多个输入图像。我们将此表示形式应用于单视图综合，这个问题更具挑战性，但可能具有更大的应用。我们的方法学会了直接从单个图像输入中预测多台图像，我们介绍了对监督的规模不变视图综合，使我们能够在在线视频上进行训练。我们显示这种方法适用于几个不同的数据集，它还生成了合理的深度图，并且它学会了填充背景层中前景对象边缘后面的内容。 项目页面https://single-view-mpi.github.io/。
A recent strand of work in view synthesis uses deep learning to generate multiplane images (a camera-centric, layered 3D representation) given two or more input images at known viewpoints. We apply this representation to single-view view synthesis, a problem which is more challenging but has potentially much wider application. Our method learns to predict a multiplane image directly from a single image input, and we introduce scale-invariant view synthesis for supervision, enabling us to train on online video. We show this approach is applicable to several different datasets, that it additionally generates reasonable depth maps, and that it learns to fill in content behind the edges of foreground objects in background layers. Project page at https://single-view-mpi.github.io/.
