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.