Google Inc.

Jonathan Chung-Kuan Huang

Matthew Alun Brown

Tal Remez

Example aspects of the present disclosure are directed to systems and methods that enable weakly-supervised learning of instance segmentation by applying a cut-and-paste technique to training of a generator model included in a generative adversarial network. In particular, the present disclosure provides a weakly-supervised approach to object instance segmentation. In some implementations, starting with known or predicted object bounding boxes, a generator model can learn to generate object masks by playing a game of cut-and-paste in an adversarial learning setup.

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Seattle, WA, United States of America

Jonathan Chung-Kuan Huang