AI RESEARCH

Boxer: Robust Lifting of Open-World 2D Bounding Boxes to 3D

arXiv CS.CV

ArXi:2604.05212v1 Announce Type: new Detecting and localizing objects in space is a fundamental computer vision problem. While much progress has been made to solve 2D object detection, 3D object localization is much less explored and far from solved, especially for open-world categories. To address this research challenge, we propose Boxer, an algorithm to estimate static 3D bounding boxes (3DBBs) from 2D open-vocabulary object detections, posed images and optional depth either represented as a sparse point cloud or dense depth.