论文标题
流动指导视频完成
Flow-edge Guided Video Completion
论文作者
论文摘要
我们提出了一种新的基于流的视频完成算法。先前的流程完成方法通常无法保留运动边界的清晰度。我们的方法首先提取并完成运动边缘，然后使用它们用锋利的边缘指导分段平滑流程的完成。现有方法在相邻帧之间的局部流连接之间传播颜色。但是，由于运动边界形成了难以穿透的障碍，并非可以以这种方式达到视频中的所有丢失区域。我们的方法通过将非本地流量连接引入时间遥远的框架来减轻此问题，从而使视频内容在运动边界上传播。我们在戴维斯数据集上验证我们的方法。视觉和定量结果都表明，我们的方法与最先进的算法进行了比较。
We present a new flow-based video completion algorithm. Previous flow completion methods are often unable to retain the sharpness of motion boundaries. Our method first extracts and completes motion edges, and then uses them to guide piecewise-smooth flow completion with sharp edges. Existing methods propagate colors among local flow connections between adjacent frames. However, not all missing regions in a video can be reached in this way because the motion boundaries form impenetrable barriers. Our method alleviates this problem by introducing non-local flow connections to temporally distant frames, enabling propagating video content over motion boundaries. We validate our approach on the DAVIS dataset. Both visual and quantitative results show that our method compares favorably against the state-of-the-art algorithms.
