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Shape Reconstruction by Learning Differentiable Surface Representations

Publications associées (36)

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Empirical study of the topology and geometry of deep networks

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Alhussein Fawzi

The goal of this paper is to analyze the geometric properties of deep neural network image classifiers in the input space. We specifically study the topology of classification regions created by deep networks, as well as their associated decision boundary. ...

2018

Large occlusion completion using normal maps

Pascal Fua, Christoph Strecha, Engin Tola, Andrea Fossati

Dense disparity maps can be computed from wide-baseline stereo pairs but will inevitably contain large areas where the depth cannot be estimated accurately because the pixels are seen in one view only. A traditional approach to this problem is to introduce ...

2010

Implicit Meshes for Effective Silhouette Handling

Pascal Fua, Mathieu Salzmann, Slobodan Ilic

Using silhouettes in uncontrolled environments typically requires handling occlusions as well as changing or cluttered backgrounds, which limits the applicability of most silhouette based methods. For the purpose of 3--D shape modeling, we show that repres ...

Springer Verlag2007

Surface parameterization and optimum design methodology for hydraulic turbines

This thesis presents a methodology for the design optimization of hydraulic runner blades. The originality of the methodology comes from the geometric definition of the blade shapes, which uses parametric surfaces instead of a set of profiles. The main adv ...

EPFL2006

Distance preserving flattening of surface sections

Roger Hersch, Laurent Saroul

Curved cross-sections extracted from medical volume images are useful for analyzing nonplanar anatomic structures such as the aorta arch or the pelvis. For visualization and for performing distance measurements, extracted surface sections need to be adequa ...

2006

Implicit Meshes Make for Better Silhouettes

Pascal Fua, Mathieu Salzmann, Slobodan Ilic

This paper advocates an implicit-surface representation of generic 3--D surfaces to take advantage of occluding edges in a very robust way. This lets us exploit silhouette constraints in uncontrolled environments that may involve occlusions and changing or ...

2004