分轮优化场景草图,让不同区域的线条自然衔接。
MROSS: Multi-Round Region-based Optimization for Scene Sketching
- 按区域分轮优化,用贝塞尔曲线逐步生成草图
- 多轮融合使线条无缝连接,提升整体连贯性
- 适合需要精细控制草图生成的设计师或研究者
场景草图旨在将复杂场景转化为简化的抽象表达,需理解场景语义并兼顾各区域特征。由于场景中前景物体、背景元素和空间划分等视觉信息多样,不同区域处理难度各异。本文将草图定义为一组贝塞尔曲线,因其平滑与灵活性。采用多轮优化策略,在每轮中对特定区域进行优化,并将新采样的笔触无缝融入前一轮生成的草图中。提出一种额外的笔触初始化方法,保障场景完整性与优化收敛性。利用基于CLIP的语义损失和基于VGG的特征损失引导优化过程。在多个数据集上的实验结果表明,该方法在草图质量与数量上均优于现有方法。
原文摘要 · Abstract (English)
Scene sketching is to convert a scene into a simplified, abstract representation that captures the essential elements and composition of the original scene. It requires a semantic understanding of the scene and consideration of different regions within the scene. Since scenes often contain diverse visual information across various regions, such as foreground objects, background elements, and spatial divisions, dealing with these different regions poses unique difficulties. In this paper, we define a sketch as some sets of Bézier curves because of their smooth and versatile characteristics. We optimize different regions of input scene in multiple rounds. In each optimization round, the strokes sampled from the next region can seamlessly be integrated into the sketch generated in the previous optimization round. We propose an additional stroke initialization method to ensure the integrity of the scene and the convergence of optimization. A novel CLIP-based Semantic Loss and a VGG-based Feature Loss are utilized to guide our multi-round optimization. Extensive experimental results on the quality and quantity of the generated sketches confirm the effectiveness of our method.
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