arXiv:2509.25857cs.GRcs.AI2025-09被引 3

用可微分轨迹生成流畅矢量草图动画,解决抖动问题。

Vector sketch animation generation with differentiable motion trajectories

  • 引入可微分运动轨迹(DMT)描述笔画点移动路径。
  • 在DAVIS和LVOS上优于现有方法,支持高帧率输出。
  • 适合需要稳定动画的创意设计与跨域生成场景。

草图是一种直接且低成本的视觉表达方式。尽管基于图像的草图已得到深入研究,但视频草图动画生成仍面临挑战,主要源于对时间连贯性的要求。本文提出一种端到端的矢量草图动画自动生成方法。为解决抖动问题,引入可微分运动轨迹(DMT)表示,通过基于多项式的轨迹描述每一帧中笔画控制点的运动。DMT实现跨多帧的全局语义梯度传播,显著提升语义一致性和时间连贯性,并支持高帧率输出。采用伯恩斯坦基函数平衡多项式参数敏感性,提高优化稳定性。不同于隐式场,采用稀疏跟踪点进行显式空间建模,提升效率并支持长时视频处理。在DAVIS和LVOS数据集上的评估表明,本方法优于当前最优技术。跨域验证在3D模型和文本到视频数据上证实了方法的鲁棒性与兼容性。

原文摘要 · Abstract (English)

Sketching is a direct and inexpensive means of visual expression. Though image-based sketching has been well studied, video-based sketch animation generation is still very challenging due to the temporal coherence requirement. In this paper, we propose a novel end-to-end automatic generation approach for vector sketch animation. To solve the flickering issue, we introduce a Differentiable Motion Trajectory (DMT) representation that describes the frame-wise movement of stroke control points using differentiable polynomial-based trajectories. DMT enables global semantic gradient propagation across multiple frames, significantly improving the semantic consistency and temporal coherence, and producing high-framerate output. DMT employs a Bernstein basis to balance the sensitivity of polynomial parameters, thus achieving more stable optimization. Instead of implicit fields, we introduce sparse track points for explicit spatial modeling, which improves efficiency and supports long-duration video processing. Evaluations on DAVIS and LVOS datasets demonstrate the superiority of our approach over SOTA methods. Cross-domain validation on 3D models and text-to-video data confirms the robustness and compatibility of our approach.

矢量动画可微分轨迹草图生成视频一致性

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