论文标题
Clipasso：语义意识的对象草图
CLIPasso: Semantically-Aware Object Sketching
论文作者
论文摘要
由于线条图的简单和最小的性质，抽象是素描的核心。抽象需要识别对象或场景的基本视觉属性，这需要语义理解和对高级概念的先验知识。因此，抽象的描述对艺术家而言是挑战，甚至对于机器而言。我们提出了Clipasso，这是一种在几何和语义简化的指导下，可以实现不同级别的抽象方法的对象草图方法。虽然草图生成方法通常依赖于明确的草图数据集进行训练，但我们利用了剪辑（对比语言图像 - 预言）的显着能力来从草图和图像中提取语义概念。我们将草图定义为一组Bézier曲线，并使用可区分的Rasterizer来优化基于剪辑的感知损失的曲线参数。抽象度通过改变中风数来控制。生成的草图在维持识别率，潜在的结构和绘制的受试者的基本视觉成分的同时，展示了多个级别的抽象。
Abstraction is at the heart of sketching due to the simple and minimal nature of line drawings. Abstraction entails identifying the essential visual properties of an object or scene, which requires semantic understanding and prior knowledge of high-level concepts. Abstract depictions are therefore challenging for artists, and even more so for machines. We present CLIPasso, an object sketching method that can achieve different levels of abstraction, guided by geometric and semantic simplifications. While sketch generation methods often rely on explicit sketch datasets for training, we utilize the remarkable ability of CLIP (Contrastive-Language-Image-Pretraining) to distill semantic concepts from sketches and images alike. We define a sketch as a set of Bézier curves and use a differentiable rasterizer to optimize the parameters of the curves directly with respect to a CLIP-based perceptual loss. The abstraction degree is controlled by varying the number of strokes. The generated sketches demonstrate multiple levels of abstraction while maintaining recognizability, underlying structure, and essential visual components of the subject drawn.
