Nozawa, N., Shum, H. P. H., Feng, Q., Ho, E. S. L. and Morishima, S. (2022) 3D car shape reconstruction from a contour sketch using GAN and lazy learning. Visual Computer, 38(4), pp. 1317-1330. (doi: 10.1007/s00371-020-02024-y)
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Abstract
3D car models are heavily used in computer games, visual effects, and even automotive designs. As a result, producing such models with minimal labour costs is increasingly more important. To tackle the challenge, we propose a novel system to reconstruct a 3D car using a single sketch image. The system learns from a synthetic database of 3D car models and their corresponding 2D contour sketches and segmentation masks, allowing effective training with minimal data collection cost. The core of the system is a machine learning pipeline that combines the use of a generative adversarial network (GAN) and lazy learning. GAN, being a deep learning method, is capable of modelling complicated data distributions, enabling the effective modelling of a large variety of cars. Its major weakness is that as a global method, modelling the fine details in the local region is challenging. Lazy learning works well to preserve local features by generating a local subspace with relevant data samples. We demonstrate that the combined use of GAN and lazy learning produces is able to produce high-quality results, in which different types of cars with complicated local features can be generated effectively with a single sketch. Our method outperforms existing ones using other machine learning structures such as the variational autoencoder.
Item Type: | Articles |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Ho, Dr Edmond S. L |
Authors: | Nozawa, N., Shum, H. P. H., Feng, Q., Ho, E. S. L., and Morishima, S. |
College/School: | College of Science and Engineering > School of Computing Science |
Journal Name: | Visual Computer |
Publisher: | Springer |
ISSN: | 0178-2789 |
ISSN (Online): | 1432-2315 |
Published Online: | 16 April 2021 |
Copyright Holders: | Copyright © 2021 The Authors |
First Published: | First published in Visual Computer 38(4): 1317-1330 |
Publisher Policy: | Reproduced under a Creative Commons License |
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