Luming Chen

EECS Department, University of California, Berkeley

Technical Report No. UCB/EECS-2020-92

May 29, 2020

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-92.pdf

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.

Advisors: John F. Canny

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BibTeX citation:

@mastersthesis{Chen:EECS-2020-92,
    Author= {Chen, Luming},
    Title= {TranSketch Dataset: Learning to Transform Sketches},
    School= {EECS Department, University of California, Berkeley},
    Year= {2020},
    Month= {May},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-92.html},
    Number= {UCB/EECS-2020-92},
    Abstract= {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.},
}

EndNote citation:

%0 Thesis
%A Chen, Luming 
%T TranSketch Dataset: Learning to Transform Sketches
%I EECS Department, University of California, Berkeley
%D 2020
%8 May 29
%@ UCB/EECS-2020-92
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-92.html
%F Chen:EECS-2020-92