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cs.CV2025
Learning Eigenstructures of Unstructured Data Manifolds
Roy Velich, Arkadi Piven, David Bensaïd +3
We introduce a novel framework that directly learns a spectral basis for shape and manifold analysis from unstructured data, eliminating the need for traditional operator selection…
cs.CV2022★ 1 cited
Partial Shape Similarity via Alignment of Multi-Metric Hamiltonian Spectra
David Bensaïd, Amit Bracha, Ron Kimmel
Evaluating the similarity of non-rigid shapes with significant partiality is a fundamental task in numerous computer vision applications. Here, we propose a novel axiomatic method…
cs.CV2021★ 1 cited
Depth Refinement for Improved Stereo Reconstruction
Amit Bracha, Noam Rotstein, David Bensaïd +2
Depth estimation is a cornerstone of a vast number of applications requiring 3D assessment of the environment, such as robotics, augmented reality, and autonomous driving to name a…