821 research outputs found
Learning Shape Priors for Single-View 3D Completion and Reconstruction
The problem of single-view 3D shape completion or reconstruction is
challenging, because among the many possible shapes that explain an
observation, most are implausible and do not correspond to natural objects.
Recent research in the field has tackled this problem by exploiting the
expressiveness of deep convolutional networks. In fact, there is another level
of ambiguity that is often overlooked: among plausible shapes, there are still
multiple shapes that fit the 2D image equally well; i.e., the ground truth
shape is non-deterministic given a single-view input. Existing fully supervised
approaches fail to address this issue, and often produce blurry mean shapes
with smooth surfaces but no fine details.
In this paper, we propose ShapeHD, pushing the limit of single-view shape
completion and reconstruction by integrating deep generative models with
adversarially learned shape priors. The learned priors serve as a regularizer,
penalizing the model only if its output is unrealistic, not if it deviates from
the ground truth. Our design thus overcomes both levels of ambiguity
aforementioned. Experiments demonstrate that ShapeHD outperforms state of the
art by a large margin in both shape completion and shape reconstruction on
multiple real datasets.Comment: ECCV 2018. The first two authors contributed equally to this work.
Project page: http://shapehd.csail.mit.edu
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A Survey of Geometric Analysis in Cultural Heritage
We present a review of recent techniques for performing geometric analysis in cultural heritage (CH) applications. The survey is aimed at researchers in the areas of computer graphics, computer vision and CH computing, as well as to scholars and practitioners in the CH field. The problems considered include shape perception enhancement, restoration and preservation support, monitoring over time, object interpretation and collection analysis. All of these problems typically rely on an understanding of the structure of the shapes in question at both a local and global level. In this survey, we discuss the different problem forms and review the main solution methods, aided by classification criteria based on the geometric scale at which the analysis is performed and the cardinality of the relationships among object parts exploited during the analysis. We finalize the report by discussing open problems and future perspectives
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