Facebook, Inc.

Ronan Alexandre Riochet

Robert D Fergus

Adam Kal Lerer

To differentiate physical and non-physical events, a discrimination system based on unsupervised machining learning is used to predict a plausibility of objects' behaviors between a starting and ending time point. The discrimination system receives a set of initial, or 'starting' content frames, each depicting a state of objects at a starting time point and an arrangement or 'behavior' of those objects at the starting time. To train the discrimination system, the first model uses the starting content frame to generate a subsequent content frame, while the second model generates a subsequent content frame without using the starting content frame. A discriminator model may thus be trained without supervision by treating the subsequent content frame generated from the first model as a possible behavior of the starting content frame, and the subsequent content frame generated from the second model as an impossible behavior of the starting content frame.

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New York, NY, United States of America

Ronan Alexandre Riochet