We introduce the Generative Query Network (GQN), a framework within which machines learn to perceive their surroundings by training only on data obtained by themselves as they move around scenes. Much like infants and animals, the GQN learns by trying to make sense of its observations of the world around it. In doing so, the GQN learns about plausible scenes and their geometrical properties, without any human labelling of the contents of scenes.
H. Nguyen, N. Nguyen, H. Doan, Z. Ahmadi, T. Doan, and L. Jiang. Proceedings of the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, New York, NY, USA, Association for Computing Machinery, (November 2022)