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Deep learning based 3D reconstruction of indoor scenes

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dc.contributor.author Hegde, Srinidhi
dc.contributor.author Anand, Saket (Advisor)
dc.contributor.author Sharma, Ojaswa (Advisor)
dc.date.accessioned 2017-11-14T08:51:04Z
dc.date.available 2017-11-14T08:51:04Z
dc.date.issued 2017-04-18
dc.identifier.uri http://repository.iiitd.edu.in/xmlui/handle/123456789/586
dc.description.abstract Recent advancement in deep learning techniques has opened doors for wide variety of applications. With growing interests in deep learning and geometry, lots of computer vision problems have been tackled using deep learning. In this work, we try to create a framework for a learning based 3D reconstruction of interiors of building from multiple 2D images that capture the entire scene of interest. We use PoseNet for regressing over the camera pose to establish spatial relationship between constituents of a scene. This work is a step towards solving a bigger problem of reconstruction from incomplete data of the scene. en_US
dc.language.iso en_US en_US
dc.subject 3D reconstruction en_US
dc.subject Deep learning en_US
dc.subject Convolutional neuural network en_US
dc.title Deep learning based 3D reconstruction of indoor scenes en_US
dc.type Other en_US


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