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arXiv · 2407.15686

Differentiable Convex Polyhedra Optimization from Multi-view Images

Daxuan Ren·Haiyi Mei·Hezi Shi·Jianmin Zheng·Jianfei Cai·Lei Yang
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Abstract

This paper presents a novel approach for the differentiable rendering of convex polyhedra, addressing the limitations of recent methods that rely on implicit field supervision. Our technique introduces a strategy that combines non-differentiable computation of hyperplane intersection through duality transform with differentiable optimization for vertex positioning with three-plane intersection, enabling gradient-based optimization without the need for 3D implicit fields. This allows for efficient shape representation across a range of applications, from shape parsing to compact mesh reconstruction. This work not only overcomes the challenges of previous approaches but also sets a new standard for representing shapes with convex polyhedra.

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Daxuan Ren, Haiyi Mei, Hezi Shi, Jianmin Zheng, Jianfei Cai, Lei Yang. 2024-07-22. Differentiable Convex Polyhedra Optimization from Multi-view Images. https://arxiv.org/abs/2407.15686

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