Bryan Russell

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Figure 1. Given a single 2D image, we predict surface normals that capture detailed object surfaces. We use the image and predicted surface normals to retrieve a 3D model from a large library of object CAD models. Abstract We introduce an approach that leverages surface normal predictions, along with appearance cues, to retrieve 3D models for objects(More)
(b)$Edge$Detec)on$ Our&Approach& Ground&Truth& Input&Image& Figure 1. Our framework used for two different pixel prediction problems with minor modification of the architecture (last layer) and training process (epochs). Note how our approach recovers the fine details missing in the ground truth segmentation (left), and achieves state-of-the-art on edge(More)
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