Neural Strokes: Stylized Line Drawing of 3D Shapes
This addresses the need for automated artistic rendering in graphics and design, offering a novel approach but with incremental improvements over prior methods.
The paper tackles the problem of generating stylized line drawings from 3D shapes by introducing a model that learns stroke variations from an artist's style, producing vector-based drawings that preserve contours and enable editing.
This paper introduces a model for producing stylized line drawings from 3D shapes. The model takes a 3D shape and a viewpoint as input, and outputs a drawing with textured strokes, with variations in stroke thickness, deformation, and color learned from an artist's style. The model is fully differentiable. We train its parameters from a single training drawing of another 3D shape. We show that, in contrast to previous image-based methods, the use of a geometric representation of 3D shape and 2D strokes allows the model to transfer important aspects of shape and texture style while preserving contours. Our method outputs the resulting drawing in a vector representation, enabling richer downstream analysis or editing in interactive applications.