Abstract:This dissertation proposes a novel framework for recovering relative depth maps from a video.
The framework is composed of two parts: a depth estimator and a sparse label interpolator. These parts are completely separate from one another and can operate independently. Prior methods have tended to heavily couple the interpolation stage with the depth estimation, which can assist with automation at the expense of flexibility. The loss of this flexibility can in fact be worse than any advantage gained by coupling… Show more
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