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In this paper we propose a pipeline for estimating 3D room layout with object and material attribute prediction using a spherical stereo image pair. We assume that the room and objects can be represented as cuboids aligned to the main axes of the room coordinate (Manhattan world). A spherical stereo alignment algorithm is proposed to align two spherical images to the global world coordinate system...
We propose an efficient algorithm to jointly estimate geometry and semantics for a given geographical region observed by multiple satellite images. Our joint estimation leverages an efficient PatchMatch inference framework defined over lattice discretization of the environment. Our cost function relies on the local planarity assumption to model scene geometry and neural network classification to determine...
In this paper, we propose an adaptive template for semantic labeling of indoor scene objects and estimating their oriented bounding facets (OBFs). The proposed adaptive template encodes prior geometric information of objects based on statistics of the training images. Given an input image, we utilize the adaptive template on the detected bounding boxes to initialize the raw labeling and OBF estimation...
We present a novel framework for estimating depth-map in a single 2D image. The proposed framework employs both vanishing point and superpixels as geometric and texture cues, respectively. The combination of both cues can generate a feasible perceptual depth-map, which will be applied to 2D to 3D image conversion.
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