Differentiable Convex Polyhedra Optimization from Multi-view Images

• URL: http://arxiv.org/abs/2407.15686v1
• Date: Mon, 22 Jul 2024 14:53:29 GMT
• Title: Differentiable Convex Polyhedra Optimization from Multi-view Images
• Authors: Daxuan Ren, Haiyi Mei, Hezi Shi, Jianmin Zheng, Jianfei Cai, Lei Yang,
• Abstract summary: This paper presents a novel approach for the differentiable rendering of convex polyhedra. It addresses the limitations of recent methods that rely on implicit field supervision.
• Score: 29.653374825428614
• License: http://creativecommons.org/licenses/by/4.0/
• 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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