In this paper, we propose an approach for view-time interpolation of stereo
videos. Specifically, we build upon X-Fields that approximates an
interpolatable mapping between the input coordinates and 2D RGB images using a
convolutional decoder. Our main contribution is to analyze and identify the
sources of the problems with using X-Fields in our application and propose
novel techniques to overcome these challenges. Specifically, we observe that
X-Fields struggles to implicitly interpolate the disparities for large baseline
cameras. Therefore, we propose multi-plane disparities to reduce the spatial
distance of the objects in the stereo views. Moreover, we propose non-uniform
time coordinates to handle the non-linear and sudden motion spikes in videos.
We additionally introduce several simple, but important, improvements over
X-Fields. We demonstrate that our approach is able to produce better results
than the state of the art, while running in near real-time rates and having low
memory and storage costs.

提出一种视图时间插值的方法，通过使用卷积解码器和 X-Fields 从输入坐标和 2D RGB 图像之间建立一个映射关系，使用多平面视差技术解决大基线相机中的视差难以隐式插值的问题，并引入非均匀时间坐标处理视频中的非线性和突然动作尖峰，改进后的方法表现优于现有技术，运行速度接近实时且存储成本低。