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A Neural Representation of Sketch Drawings

11 Apr 2017ICLR 2018 1arXiv:1704.03477archive 2025-07-28

David Ha, Douglas Eck

We present sketch-rnn, a recurrent neural network (RNN) able to construct stroke-based drawings of common objects. The model is trained on thousands of crude human-drawn images representing hundreds of classes. We outline a framework for conditional and unconditional sketch generation, and describe new robust training methods for generating coherent sketch drawings in a vector format.

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18 repositories listed; official and paper-mentioned ones first.

Ar-Kareem/sketch-RNN mentioned on GitHubpytorch report
MarioBonse/Sketch-rnn mentioned on GitHubtf report
Triple-L/Wartegg_test mentioned on GitHub report
XDUWQ/sketch-rnn-pytorch mentioned on GitHubpytorch report
abel-leulseged/Quick-Draw mentioned on GitHub report
alexis-jacq/Pytorch-Sketch-RNN mentioned on GitHubpytorch report
altsoph/paranoid_transformer mentioned on GitHubpytorch report
city535353/sketch_rnn mentioned on GitHubtf report
cpmpercussion/keras-mdn-layer mentioned on GitHubtf report
eyalzk/sketch_rnn_keras mentioned on GitHubtf report
hardmaru/sketch-rnn-datasets mentioned on GitHubtf report
hardmaru/sketch-rnn-flowchart mentioned on GitHubtf report
kumnikhil/christmAIs_replica mentioned on GitHubtf report
nn210/SketchRNNIntroToML mentioned on GitHubtf report
thinkingmachines/christmAIs mentioned on GitHubtf report
tosmaster/imagevision mentioned on GitHubpytorch report
yurangja99/Pytorch-Sketch-RNN mentioned on GitHubpytorch report
labmlai/annotated_deep_learning_paper_implementations pytorch report

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Quick, Draw! DatasetQuickDraw

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