跨实例高斯点云对齐 via 几何感知特征引导对齐
Cross-Instance Gaussian Splatting Registration via Geometry-Aware Feature-Guided Alignment
AI总结：
本文提出GSA方法，通过相似变换对齐不同类别的3DGS模型，无需真实尺度输入，通过迭代特征引导绝对对齐和多视图特征一致性优化，实现跨实例对齐。
摘要：
我们提出了高斯点云对齐（GSA），一种新颖的方法，通过相似变换（旋转、平移和缩放）对齐两个独立的3D高斯点云（3DGS）模型，即使它们属于同一类别但不同对象（例如不同汽车）。与现有方法不同，现有方法只能对齐相同对象的3DGS模型（例如同一辆汽车），并且通常必须给出真实尺度作为输入，而我们成功地估计了它。GSA利用视角引导的球面图特征来获得稳健的对应关系，并引入了一个两步优化框架，该框架在对齐3DGS模型的同时保持它们固定。首先，我们应用迭代特征引导的绝对对齐求解器作为粗略对齐，它对糟糕的初始化（例如180度偏移或10倍缩放差距）具有鲁棒性。其次，我们使用细对齐步骤，通过受逆辐射场公式的启发，强制多视图特征一致性。第一步已经实现了最先进的性能，第二步进一步改进了结果。在相同对象的情况下，GSA优于先前的工作，即使当其他方法被给予真实尺度时，也经常有显著优势。在更困难的不同对象同一类别的情况下，GSA远远超越它们，提供了首个有效的解决方案，用于类别级别的3DGS对齐，并解锁了新的应用。项目网页：https://bgu-cs-vil.github.io/GSA-project/
英文摘要：
We present Gaussian Splatting Alignment (GSA), a novel method for aligning two independent 3D Gaussian Splatting (3DGS) models via a similarity transformation (rotation, translation, and scale), even when they are of different objects in the same category (e.g., different cars). In contrast, existing methods can only align 3DGS models of the same object (e.g., the same car) and often must be given true scale as input, while we estimate it successfully. GSA leverages viewpoint-guided spherical map features to obtain robust correspondences and introduces a two-step optimization framework that aligns 3DGS models while keeping them fixed. First, we apply an iterative feature-guided absolute orientation solver as our coarse registration, which is robust to poor initialization (e.g., 180 degrees misalignment or a 10x scale gap). Next, we use a fine registration step that enforces multi-view feature consistency, inspired by inverse radiance-field formulations. The first step already achieves state-of-the-art performance, and the second further improves results. In the same-object case, GSA outperforms prior works, often by a large margin, even when the other methods are given the true scale. In the harder case of different objects in the same category, GSA vastly surpasses them, providing the first effective solution for category-level 3DGS registration and unlocking new applications. Project webpage: https://bgu-cs-vil.github.io/GSA-project/
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
