Guided neural style transfer for shape stylization

PloS One
Gantugs AtarsaikhanSeiichi Uchida

Abstract

Designing logos, typefaces, and other decorated shapes can require professional skills. In this paper, we aim to produce new and unique decorated shapes by stylizing ordinary shapes with machine learning. Specifically, we combined parametric and non-parametric neural style transfer algorithms to transfer both local and global features. Furthermore, we introduced a distance-based guiding to the neural style transfer process, so that only the foreground shape will be decorated. Lastly, qualitative evaluation and ablation studies are provided to demonstrate the usefulness of the proposed method.

References

Sep 20, 2017·Current Opinion in Neurobiology·Leon A GatysMatthias Bethge
Jun 11, 2019·IEEE Transactions on Visualization and Computer Graphics·Yongcheng JingMingli Song
Nov 2, 2019·IEEE Transactions on Visualization and Computer Graphics·Reza Adhitya SaputraPaul Asente

Related Concepts

Evaluation
Shapes
Ablation

Trending Feeds

COVID-19

Coronaviruses encompass a large family of viruses that cause the common cold as well as more serious diseases, such as the ongoing outbreak of coronavirus disease 2019 (COVID-19; formally known as 2019-nCoV). Coronaviruses can spread from animals to humans; symptoms include fever, cough, shortness of breath, and breathing difficulties; in more severe cases, infection can lead to death. This feed covers recent research on COVID-19.

Synthetic Genetic Array Analysis

Synthetic genetic arrays allow the systematic examination of genetic interactions. Here is the latest research focusing on synthetic genetic arrays and their analyses.

Neural Activity: Imaging

Imaging of neural activity in vivo has developed rapidly recently with the advancement of fluorescence microscopy, including new applications using miniaturized microscopes (miniscopes). This feed follows the progress in this growing field.

Computational Methods for Protein Structures

Computational methods employing machine learning algorithms are powerful tools that can be used to predict the effect of mutations on protein structure. This is important in neurodegenerative disorders, where some mutations can cause the formation of toxic protein aggregations. This feed follows the latests insights into the relationships between mutation and protein structure leading to better understanding of disease.

Congenital Hyperinsulinism

Congenital hyperinsulinism is caused by genetic mutations resulting in excess insulin secretion from beta cells of the pancreas. Here is the latest research.

Chronic Fatigue Syndrome

Chronic fatigue syndrome is a disease characterized by unexplained disabling fatigue; the pathology of which is incompletely understood. Discover the latest research on chronic fatigue syndrome here.

Epigenetic Memory

Epigenetic memory refers to the heritable genetic changes that are not explained by the DNA sequence. Find the latest research on epigenetic memory here.

Cell Atlas of the Human Eye

Constructing a cell atlas of the human eye will require transcriptomic and histologic analysis over the lifespan. This understanding will aid in the study of development and disease. Find the latest research pertaining to the Cell Atlas of the Human Eye here.

Femoral Neoplasms

Femoral Neoplasms are bone tumors that arise in the femur. Discover the latest research on femoral neoplasms here.

Related Papers

Chemphyschem : a European Journal of Chemical Physics and Physical Chemistry
Xiuting LiRichard G Compton
© 2021 Meta ULC. All rights reserved