Neural Modelling of Flower Bas‐relief from 2D Line Drawing
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Date
2021
Journal Title
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© 2021 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd
Abstract
Different from other types of bas‐reliefs, a flower bas‐relief contains a large number of depth‐discontinuity edges. Most existing line‐based methods reconstruct free‐form surfaces by ignoring the depth‐discontinuities, thus are less efficient in modeling flower bas‐reliefs. This paper presents a neural‐based solution which benefits from the recent advances in CNN. Specially, we use line gradients to encode the depth orderings at leaf edges. Given a line drawing, a heuristic method is first proposed to compute 2D gradients at lines. Line gradients and dense curvatures interpolated from sparse user inputs are then fed into a neural network, which outputs depths and normals of the final bas‐relief. In addition, we introduce an object‐based method to generate flower bas‐reliefs and line drawings for network training. Extensive experiments show that our method is effective in modelling bas‐reliefs with depth‐discontinuity edges. User evaluation also shows that our method is intuitive and accessible to common users.
Description
@article{10.1111:cgf.14273,
journal = {Computer Graphics Forum},
title = {{Neural Modelling of Flower Bas‐relief from 2D Line Drawing}},
author = {Zhang, Yu‐Wei and Wang, Jinlei and Wang, Wenping and Chen, Yanzhao and Liu, Hui and Ji, Zhongping and Zhang, Caiming},
year = {2021},
publisher = {© 2021 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd},
ISSN = {1467-8659},
DOI = {10.1111/cgf.14273}
}