In the realm of computer vision and graphics accurately establishing correspondences
between geometric 3D shapes is pivotal for applications like object tracking registration …

We propose a novel zero-shot approach to computing correspondences between 3D
shapes. Existing approaches mainly focus on isometric and near-isometric shape pairs (eg …

Abstract The Laplace-Beltrami operator (LBO) emerges from studying manifolds equipped
with a Riemannian metric. It is often called the swiss army knife of geometry processing as it …

In this work we propose to combine the advantages of learning-based and combinatorial
formalisms for 3D shape matching. While learning-based methods lead to state-of-the-art …

Abstract We present Shape Non-rigid Kinematics (SNK), a novel zero-shot method for non-
rigid shape matching that eliminates the need for extensive training or ground truth data …

In this paper, we present a novel pipeline to compute and refine a data-driven solution for
estimating the correspondence between 3D point clouds. Our method is compatible with the …

Finding shortest paths on product spaces is a popular approach to tackle numerous variants
of matching problems including the dynamic time warping method for matching signals the …

Learning functions defined on non‐flat domains, such as outer surfaces of non‐rigid shapes,
is a central task in computer vision and geometry processing. Recent studies have explored …

Deep functional maps have emerged in recent years as a prominent learning-based
framework for non-rigid shape matching problems. While early methods in this domain only …

Although 3D shape matching and interpolation are highly interrelated they are often studied
separately and applied sequentially to relate different 3D shapes thus resulting in sub …