Dense Object Reconstruction from RGBD Images with Embedded Deep Shape Representations

With an application to dense object modeling from RGB-D images, our work aims at taking the best of both worlds by embedding modern higher-order object shape priors into classical iterative residual minimization objectives. We demonstrate a general ability to improve mapping accuracy with respect to each modality alone, and present a successful application to real data.