Go to main content

PDF

Description

This report introduces a new dataset TranSketch, which is a collection of 20,032 tree sketch pairs, each accompanied with a natural language description describing the instructions needed to transform one sketch to the other. To provide more options for exploration, for each sketch, we also include a latent representation produced by the encoder of a Sketch-RNN model. The TranSketch dataset provides fine-grain transformation between stroke-based sketch pairs using stylistic content text descriptions. Our statistical analysis suggests tree component-level transformation to be the most promising direction for investigation, but there are certainly more to be explored for this dataset.

Details

Title
TranSketch Dataset: Learning to Transform Sketches
Creator
Chen, Luming, Author
Published
2020-05-29
Full Collection Name
Electrical Engineering & Computer Sciences Technical Reports
Type
Text
Format
technical reports
Extent
26 p
Language
eng
Usage Statement
Researchers may make free and open use of the UC Berkeley Library’s digitized public domain materials. However, some materials in our online collections may be protected by U.S. copyright law (Title 17, U.S.C.). Use or reproduction of materials protected by copyright beyond that allowed by fair use (Title 17, U.S.C. § 107) requires permission from the copyright owners. The use or reproduction of some materials may also be restricted by terms of University of California gift or purchase agreements, privacy and publicity rights, or trademark law. Responsibility for determining rights status and permissibility of any use or reproduction rests exclusively with the researcher. To learn more or make inquiries, please see our permissions policies (https://www.lib.berkeley.edu/about/permissions-policies).
Collection

Files

Statistics

from
to
Export
Download Full History
Download
Formats
Format
BibTeX
MARCXML
TextMARC
MARC
DublinCore
EndNote
NLM
RefWorks
RIS
Add to Basket