Crypt | 2020
Sketch-Gen presents a generative recurrent neural network (RNN) capable of producing sketches of common objects, with the goal of training a machine to draw and generalise abstract concepts in a manner similar to humans. It is able to construct stroke-based drawings of common objects in vector format. The model is trained on human-drawn images of different classes. As a first step towards this goal, we train our model on a dataset of hand-drawn sketches, each represented as a sequence of motor actions controlling a pen: which direction to move, when to lift the pen up, and when to stop drawing. In doing so, we created a model that potentially has many applications, from assisting the creative process of an artist, to helping teach students how to draw.