Transcription of Multi-view 3D Object Reconstruction …
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Multi-view 3D Object Reconstruction …
3D-R2N2: A Unified Approach for Single andMulti- view 3D Object ReconstructionChristopher B. Choy Danfei Xu?JunYoung Gwak?Kevin Chen Silvio SavareseStanford University{chrischoy, danfei, jgwak, kchen92, by the recent success of methods that employ shapepriors to achieve robust 3D reconstructions, we propose a novel recurrentneural network architecture that we call the 3D Recurrent Reconstruc-tion Neural Network (3D-R2N2). The network learns a mapping fromimages of objects to their underlying 3D shapes from a large collectionof synthetic data [1]. Our network takes in one or more images of an ob-ject instance from arbitrary viewpoints and outputs a Reconstruction ofthe Object in the form of a 3D occupancy grid. Unlike most of the previ-ous works, our network does not require any image annotations or objectclass labels for training or testing.}
3D-R2N2: A Uni ed Approach for Single and Multi-view 3D Object Reconstruction Christopher B. Choy Danfei Xu?JunYoung Gwak Kevin Chen Silvio Savarese
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