MannequinChallenge: Learning the Depths of Moving People by Watching Frozen People
IEEE transactions on pattern analysis and machine intelligence, pp. 1-1, 2020.
We present a method for predicting dense depth in scenarios where both a monocular camera and people in the scene are freely moving. Existing methods for recovering depth for dynamic, non-rigid objects from monocular video impose strong assumptions on the objects' motion and may only recover sparse depth. In this paper, we take a data-dri...More
PPT (Upload PPT)