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 …

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 …

In this paper, we propose a learning-based framework for non-rigid shape registra-tion
without correspondence supervision. Traditional shape registration techniques typically rely …

In this paper, we propose a learning-based framework for non-rigid shape registration
without correspondence supervision. Traditional shape registration techniques typically rely …

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

In this paper, we propose a novel learning-based framework for non-rigid point cloud
matching, which can be trained purely on point clouds without any correspondence …

Aligning a template to 3D human point clouds is a long-standing problem crucial for tasks
like animation, reconstruction, and most supervised learning pipelines. Recent data-driven …