Newest papers

Learning from Automatic 3D Gaussian Splatting Edits for Online Bayesian Scene Change Detection

Changrui Zhu, Simon Julier · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.28490 · cited by 0 works (OpenAlex) · open-access PDF

Chinese

在线场景变化的检测需要整合到来的观察来确定哪些地区与参考场景相比发生了变化。我们更新了改变的信念,因为新图像使用通用Bayesian证据合并而来。然而,变化和证据模型的先前概率是未知的,数字Bayesian推断可以是昂贵的。我们通过从自动编辑到参考3D Gaussian Splatting(3DGS)模型进行离线学习来解决这些挑战。这些编辑产生了没有手动注释的标签培训视图。与未改变的参考观察一起,它们为学习场景特定的证据模型提供监督,并估计有效的像素先前和响应统计。在线预测将当前证据与历史支持相结合,而封闭式Bayes局部因素,通过学习响应

Machine translation (Meta M2M100); the English original follows.

Abstract

Online scene change detection requires integrating incoming observations to determine which regions have changed relative to a reference scene. We update change beliefs as new images arrive using generalised Bayesian evidence fusion. However, the prior probability of change and evidence models are unknown beforehand, and numerical Bayesian inference can be costly. We address these challenges by learning offline from automatic edits to a reference 3D Gaussian Splatting (3DGS) model. These edits generate labelled training views without manual annotations. Together with unchanged reference observations, they provide supervision for learning scene-specific evidence models and estimating the effective pixel prior and response statistics. Online prediction combines current evidence with historical support, while closed-form local Bayes factors, parameterized by the learned response statistics, update an accumulated 3D Gaussian field. Object-guided refinement produces the final change masks. Our method achieves state-of-the-art accuracy on PASLCD and CCS3D, with $67.64\%$ and $75.82\%$ mIoU, respectively. On PASLCD, the complete pipeline runs at $17.2$\,FPS over complete query sequences, the fastest among the evaluated online methods.

Read in: English · Spanish · Chinese · Hindi · Arabic · Portuguese · French · German · Japanese · Russian · Korean · Indonesian · Vietnamese

Topics: Computer science, Change detection, Artificial intelligence, Bayesian probability, Inference, Gaussian process

Sources: OpenAlex (CC0), arXiv, Crossref. Agent Exchange