TexHOI:在单目手-物体交互场景中重建三维未知物体的纹理。

Alakh Aggarwal, Ningna Wang, Xiaohu Guo
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引用次数: 0

摘要

从单目帧序列中重建具有高保真纹理的动态真实物体的三维模型是近年来一个具有挑战性的问题。这种困难源于阴影、间接照明以及由于手-物相互作用造成的不准确的物体姿态估计等因素。为了解决这些挑战,我们提出了一种新的方法来预测手对环境能见度和物体表面反照率的间接照明的影响。我们的方法首先通过对亮度场的复合渲染来学习物体、手和背景的几何形状和低保真纹理。同时,我们优化了手和物体的姿态,以实现准确的物体姿态估计。然后,我们改进基于物理的渲染参数——包括粗糙度、镜面、反照率、手部可见性、肤色反射和环境照明——以产生精确的反照率、准确的手部照明和阴影区域。我们的方法超越了最先进的纹理重建方法,据我们所知,是第一个在物体纹理重建中考虑手-物体相互作用的方法。请登录https://alakhag.github.io/TexHOI-website/查看我们的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TexHOI: Reconstructing Textures of 3D Unknown Objects in Monocular Hand-Object Interaction Scenes.

Reconstructing 3D models of dynamic, real-world objects with high-fidelity textures from monocular frame sequences has been a challenging problem in recent years. This difficulty stems from factors such as shadows, indirect illumination, and inaccurate object-pose estimations due to occluding hand-object interactions. To address these challenges, we propose a novel approach that predicts the hand's impact on environmental visibility and indirect illumination on the object's surface albedo. Our method first learns the geometry and low-fidelity texture of the object, hand, and background through composite rendering of radiance fields. Simultaneously, we optimize the hand and object poses to achieve accurate object-pose estimations. We then refine physics-based rendering parameters-including roughness, specularity, albedo, hand visibility, skin color reflections, and environmental illumination-to produce precise albedo, and accurate hand illumination and shadow regions. Our approach surpasses state-of-the-art methods in texture reconstruction and, to the best of our knowledge, is the first to account for hand-object interactions in object texture reconstruction. Please check our work at: https://alakhag.github.io/TexHOI-website/.

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