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Neural Strokes: Stylized Line Drawing of 3D Shapes

2021-10-08 05:40:57
Difan Liu, Matthew Fisher, Aaron Hertzmann, Evangelos Kalogerakis

Abstract

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.

Abstract (translated)

URL

https://arxiv.org/abs/2110.03900

PDF

https://arxiv.org/pdf/2110.03900.pdf


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