We propose a novel deep learning-based method, called mesh superresolution, to enrich low-resolution (LR) cloth meshes with wrinkles. A pair of low and high-resolution (HR) meshes are simulated, with the simulation of the HR mesh tracks with that of the LR mesh. The frame data are converted into geometry images and used as a training data set. A residual network, called SR residual network, is employed to train an image synthesizer that superresolves an LR image into an HR one. Once the HR image is converted back to an HR mesh, it is abundant in wrinkles compared with its coarse counterpart. The synthesizing is very efficient and is 24× faster than a full HR simulation. We demonstrate the performances of mesh superresolution with various simulation scenes.
a) (b) Figure 1: (a) Fitting a set of garments onto a human body. (b) Bending and straightening an arm: the sleeve is pinched and released.
AbstractWe present an efficient and stable framework, called Unified Intersection Resolver (UIR), for cloth simulation systems where not only impending collisions but also pre-existing penetrations often arise. These two types of collisions are handled in a unified manner, by detecting edge-face intersections first and then forming penetration stencils to be resolved iteratively. A stencil is a quadruple of vertices and it reveals either a vertex-face or an edge-edge collision event happened. Each quadruple also implicitly defines a collision normal, through which the four stencil vertices can be relocated, so that the corresponding edge-face intersection disappear. We deduce three different ways, i.e., from predefined surface orientation, from history data and from global intersection analysis, to determine the collision normals of these stencils robustly. Multiple stencils that constitute a penetration region are processed simultaneously to eliminate penetrations. Cloth trapped in pinched environmental objects can be handled easily within our framework. We highlight its robustness by a number of challenging experiments involving collisions.
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