Sketch Video Synthesis

GenAI SCCE Inpainting CV ODBO Backbone
2023年11月26日
理解语义细节和高级概念对于图像草图生成至关重要,当应用于视频领域时,这一挑战变得更加艰巨。为了解决这个问题,我们提出了一种基于优化的框架,用于绘制以逐帧Bézier曲线表示的视频草图。具体而言,我们首先提出了一种跨帧笔画初始化方法,以热身每个曲线的位置和宽度。然后,我们利用基于CLIP特征的语义损失和使用自分解2D图集网络设计的一致性损失来优化这些曲线的位置。基于这些设计元素,生成的草图视频展现出令人印象深刻的视觉抽象和时间上的连贯性。此外,通过将视频通过草图过程转换为SVG线条,我们的方法还可以在基于草图的视频编辑和视频涂鸦中发挥作用,通过视频合成实现,正如预告片所展示的。
Understanding semantic intricacies and high-level concepts is essential in image sketch generation, and this challenge becomes even more formidable when applied to the domain of videos. To address this, we propose a novel optimization-based framework for sketching videos represented by the frame-wise B\'ezier curve. In detail, we first propose a cross-frame stroke initialization approach to warm up the location and the width of each curve. Then, we optimize the locations of these curves by utilizing a semantic loss based on CLIP features and a newly designed consistency loss using the self-decomposed 2D atlas network. Built upon these design elements, the resulting sketch video showcases impressive visual abstraction and temporal coherence. Furthermore, by transforming a video into SVG lines through the sketching process, our method unlocks applications in sketch-based video editing and video doodling, enabled through video composition, as exemplified in the teaser.
许愿