Differentiable Convex Polyhedra Optimization from Multi-view Images
<|reference_start|>Differentiable Convex Polyhedra Optimization from Multi-view Images: 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.<|reference_end|>
@article{ren2024differentiable,
    title={Differentiable Convex Polyhedra Optimization from Multi-view Images},
    author={Daxuan Ren, Haiyi Mei, Hezi Shi, Jianmin Zheng, Jianfei Cai, Lei Yang},
    journal={arXiv preprint arXiv:2407.15686},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.15686},
    primaryClass={cs.GR cs.CV}
}