Our team of artists and machine learning researchers designed a creative algorithm that can generate authentic sculptural artworks. These artworks do not mimic any given forms and cannot be easily categorized into the dataset categories. Our approach extends DeepDream from images to 3D point clouds. The proposed algorithm, Amalgamated DeepDream (ADD), leverages the properties of point clouds to create objects with better quality than the naive extension. ADD presents promise for the creativity of machines, the kind of creativity that pushes artists to explore novel methods or materials and to create new genres instead of creating variations of existing forms or styles within one genre. For example, from Realism to Abstract Expressionism, or to Minimalism. Lastly, we present the sculptures that are 3D printed based on the point clouds created by ADD.
@article{arxiv.1811.05389,
title = {Hallucinating Point Cloud into 3D Sculptural Object},
author = {Chun-Liang Li and Eunsu Kang and Songwei Ge and Lingyao Zhang and Austin Dill and Manzil Zaheer and Barnabas Poczos},
journal= {arXiv preprint arXiv:1811.05389},
year = {2018}
}
Comments
Accepted by Second Workshop on Machine Learning for Creativity and Design, NIPS 2018