Kavli Affiliate: Matthew Fisher
| First 5 Authors: Sanghyun Son, Matheus Gadelha, Yang Zhou, Matthew Fisher, Zexiang Xu
| Summary:
Recent probabilistic methods for 3D triangular meshes capture diverse shapes
by differentiable mesh connectivity, but face high computational costs with
increased shape details. We introduce a new differentiable mesh processing
method in 2D and 3D that addresses this challenge and efficiently handles
meshes with intricate structures. Additionally, we present an algorithm that
adapts the mesh resolution to local geometry in 2D for efficient
representation. We demonstrate the effectiveness of our approach on 2D point
cloud and 3D multi-view reconstruction tasks. Visit our project page
(https://sonsang.github.io/dmesh2-project) for source code and supplementary
material.
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