Seminar

Abstract: Objects can be represented in various forms, including meshes, point clouds, parameterizations, and neural implicits. Traditionally, many algorithms are limited to a single specific representation. We focus on geometry processing with any representation supporting closest-point queries, making these methods universally applicable. Furthermore, objects can be manifold or nonmanifold, open or closed, orientable or not, and [...]

Abstract: Kinematic rigs make 3D meshes editable, but they do not specify which poses are plausible for a given asset. As a result, naively manipulating rig parameters can easily produce unrealistic deformations. Artists often address this by manually authoring pose spaces, but doing so requires substantial effort and expertise. In this talk, I will first give [...]

Abstract: Geometry can make AI approaches more accurate, efficient and controllable. In this talk, we cover three contributions that demonstrate this. The first is DeltaConv, a building block for CNNs on curved surfaces. DeltaConv works directly on the surface, rather than in 3D space. That means the networks can be more efficient and robust to deformations [...]

Abstract: Cancer rarely announces itself. It hints. It hides. Radiologists often describe their work as looking for needles in a haystack. By the time we are certain, it is often too late. Artificial intelligence (AI) offers a fundamentally new approach to this problem. By learning complex statistical patterns from large collections of medical images and clinical [...]