aigc3d/glob3r

Glob3R is the official repository for a research paper called Glob3R: Global Structure-from-Motion With 3D Foundation Models, produced by researchers from HKUST's Spatial Artificial Intelligence Lab along with Alibaba Group and two universities. Structure-from-motion is a computer vision technique that reconstructs the 3D shape of a scene and the positions of the cameras that captured it, using a set of photos as input. According to the README, Glob3R is a method for doing this reconstruction at scale by building on existing geometric foundation models. It takes dense predictions from those models and turns them into reliable tracked points across multiple images, then refines both the camera positions and the 3D scene geometry using techniques called motion averaging and bundle adjustment. The authors say this improves accuracy and consistency compared to prior methods, especially on long video sequences, large scenes, and collections of photos that were not taken in any particular order. The repository itself is currently very sparse. The README includes a to-do list showing that the inference code and evaluation scripts have not been released yet, so at this point the repository mainly serves as a landing page pointing to the paper on arXiv and a project website, along with citation information and acknowledgements to several other research projects that inspired parts of the design. Those acknowledged projects cover related work on evaluation, feature matching, and reconstruction pipelines, suggesting Glob3R combines and extends ideas from several existing tools rather than starting from nothing. No license is stated, and there is no runnable code included yet, so anyone wanting to try the method firsthand will need to wait for a future update to this repository.