International audienceWe propose a novel pointwise descriptor, called DWKS, aimed at finding correspondences across two deformable shape collections. Unlike the majority of existing descriptors, rather than capturing local geometry, DWKS captures the deformation around a point within a collection in a multi-scale and informative manner. This, in turn, allows to compute inter-collection correspondences without using landmarks. To this end, we build upon the successful spectral WKS descriptors, but rather than using the Laplace-Beltrami operator, show that a similar construction can be performed on shape difference operators, that capture differences or distortion within a collection. By leveraging the collection information our descriptor fa...
To appear in Proceedings of the Thirty-fifth Annual Conference on Neural Information Processing Syst...
International audienceThis paper presents a shape representation and a variational framework for the...
We propose a shape matching method that produces dense correspondences tuned to a specific class of ...
International audienceWe propose a novel pointwise descriptor, called DWKS, aimed at finding corresp...
We propose novel point descriptors for 3D shapes with the potential to match two shapes representing...
In this thesis, we address the challenge of computing correspondences between dissimilar shapes. Thi...
We propose novel point descriptors for 3D shapes with the potential to match two shapes representing...
We present a method to match three dimensional shapes under non-isometric deformations, topology cha...
We propose a novel framework to build descriptors of local intensity that are invariant to general d...
We present a new local descriptor for 3D shapes, directly applicable to a wide range of shape analys...
We propose a novel framework to build descriptors of local intensity that are invariant to general d...
International audienceWe present a new deep learning approach for matching deformable shapes by intr...
International audienceWe present a robust method to find region-level correspondences between shapes...
International audienceComparing points on 3D shapes is among the fundamental operations in shape ana...
Establishing correspondences between salient points on 3D shapes results in a function mapping simil...
To appear in Proceedings of the Thirty-fifth Annual Conference on Neural Information Processing Syst...
International audienceThis paper presents a shape representation and a variational framework for the...
We propose a shape matching method that produces dense correspondences tuned to a specific class of ...
International audienceWe propose a novel pointwise descriptor, called DWKS, aimed at finding corresp...
We propose novel point descriptors for 3D shapes with the potential to match two shapes representing...
In this thesis, we address the challenge of computing correspondences between dissimilar shapes. Thi...
We propose novel point descriptors for 3D shapes with the potential to match two shapes representing...
We present a method to match three dimensional shapes under non-isometric deformations, topology cha...
We propose a novel framework to build descriptors of local intensity that are invariant to general d...
We present a new local descriptor for 3D shapes, directly applicable to a wide range of shape analys...
We propose a novel framework to build descriptors of local intensity that are invariant to general d...
International audienceWe present a new deep learning approach for matching deformable shapes by intr...
International audienceWe present a robust method to find region-level correspondences between shapes...
International audienceComparing points on 3D shapes is among the fundamental operations in shape ana...
Establishing correspondences between salient points on 3D shapes results in a function mapping simil...
To appear in Proceedings of the Thirty-fifth Annual Conference on Neural Information Processing Syst...
International audienceThis paper presents a shape representation and a variational framework for the...
We propose a shape matching method that produces dense correspondences tuned to a specific class of ...