We propose a novel reference-based video colorization framework with spatiotemporal correspondence. Reference-based methods colorize grayscale frames referencing a user input color frame. Existing methods suffer from the color leakage between objects and the emergence of average colors, derived from non-local semantic correspondence in space. To address this issue, we warp colors only from the regions on the reference frame restricted by correspondence in time. We propagate masks as temporal correspondences, using two complementary tracking approaches: off-the-shelf instance tracking for high performance segmentation, and newly proposed dense tracking to track various types of objects. By restricting temporally-related regions for referencing colors, our approach propagates faithful colors throughout the video. Experiments demonstrate that our method outperforms state-of-the-art methods quantitatively and qualitatively.

翻译：我们提出一个新的基于参考的视频色彩化框架,使用时空通信。基于参考的方法将灰度框架颜色化,为用户输入的颜色框架提供参照。现有的方法因物体之间的颜色泄漏和来自空间非本地语义通信的平均颜色的出现而受到影响。为了解决这一问题,我们只在时间通信限制的参考框架中从区域扭曲颜色。我们使用两种互补的跟踪方法,将面具作为时间通信传播,使用两种互补的跟踪方法:高性能分解的现成实例跟踪,以及新提出的大量跟踪跟踪以跟踪各种类型的物体。通过限制与时间有关的区域以查找颜色,我们的方法在整个视频中传播忠实的颜色。实验表明,我们的方法在数量上和质量上优于最先进的方法。