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Our main insight is that instead of attempting to recover precise geometry, we statistically model<jats:italic>geometric classes<\/jats:italic>defined by their orientations in the scene. Our algorithm labels regions of the input image into coarse categories: \"ground\", \"sky\", and \"vertical\". These labels are then used to \"cut and fold\" the image into a pop-up model using a set of simple assumptions. Because of the inherent ambiguity of the problem and the statistical nature of the approach, the algorithm is not expected to work on every image. 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