In contrast, we propose an innovative 3D Modulated Morphable Model (3D3M) to learn the dense shape correspondence from monocular images in a self-supervised manner. Specifically, given a batch of ...

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This activity is supported by DFT calculations comparing single-atom models of the Cu active site to nanoparticle models, which predict nanoparticles to be more selective for dimerization to ...

The estimate is achieved by fitting a statistical, morphable model of 3D faces to images. The model is learned from a set of textured 3D scans of heads. We describe the construction of the morphable ...