The goal of this paper is to learn dense 3D shape correspondence for topology-varying objects in an unsupervised manner. Our method is trained in three stages: 1) PointNet like encoder and implicit ...

Until now we have considered methods for computing derivatives that work directly on the function being differentiated. However, this is not always possible. For example, if the function can only be ...

Abstract: Recently, the single image super-resolution based on implicit image function is a hot topic, which learns a universal model for arbitrary upsampling scales. By contrast, color-guided depth ...

Prior to every geostatistical estimation or simulation study there is a need for delimiting the geologic domains of the deposit, which is traditionally done manually by a geomodeler in a laborious, ...