4 papers
SceneCAD: Predicting Object Alignments and Layouts in RGB-D Scans
Armen Avetisyan, Tatiana Khanova, Christopher Choy +3
We present a novel approach to reconstructing lightweight, CAD-based representations of scanned 3D environments from commodity RGB-D sensors. Our key idea is to jointly optimize fo…
RIO: 3D Object Instance Re-Localization in Changing Indoor Environments
Johanna Wald, Armen Avetisyan, Nassir Navab +2
In this work, we introduce the task of 3D object instance re-localization (RIO): given one or multiple objects in an RGB-D scan, we want to estimate their corresponding 6DoF poses…
End-to-End CAD Model Retrieval and 9DoF Alignment in 3D Scans
Armen Avetisyan, Angela Dai, Matthias Nießner
We present a novel, end-to-end approach to align CAD models to an 3D scan of a scene, enabling transformation of a noisy, incomplete 3D scan to a compact, CAD reconstruction with c…
Scan2CAD: Learning CAD Model Alignment in RGB-D Scans
Armen Avetisyan, Manuel Dahnert, Angela Dai +3
We present Scan2CAD, a novel data-driven method that learns to align clean 3D CAD models from a shape database to the noisy and incomplete geometry of a commodity RGB-D scan. For a…