@inproceedings{9783ef3b9e88463193608e1ae0f240e4,
title = "Interactive 3D Modeling with a Generative Adversarial Network",
abstract = "We propose the idea of using a generative adversarial network (GAN) to assist users in designing real-world shapes with a simple interface. Users edit a voxel grid with a Minecraft-like interface. Yet they can execute a SNAP command at any time, which transforms their rough model into a desired shape that is both similar and realistic. They can edit and snap until they are satisfied with the result. The advantage of this approach is to assist novice users to create 3D models characteristic of the training data by only specifying rough edits. Our key contribution is to create a suitable projection operator around a 3D-GAN that maps an arbitrary 3D voxel input to a latent vector in the shape manifold of the generator that is both similar in shape to the input but also realistic. Experiments show our method is promising for computer-Assisted interactive modeling.",
keywords = "Computer-Graphics, GAN, Interactive-Modeling, Voxel",
author = "Jerry Liu and Fisher Yu and Thomas Funkhouser",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 7th IEEE International Conference on 3D Vision, 3DV 2017 ; Conference date: 10-10-2017 Through 12-10-2017",
year = "2018",
month = may,
day = "25",
doi = "10.1109/3DV.2017.00024",
language = "English (US)",
series = "Proceedings - 2017 International Conference on 3D Vision, 3DV 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "126--134",
booktitle = "Proceedings - 2017 International Conference on 3D Vision, 3DV 2017",
address = "United States",
}