1 code implementation • NeurIPS 2021 • Manuel Dahnert, Ji Hou, Matthias Nießner, Angela Dai
Inspired by 2D panoptic segmentation, we propose to unify the tasks of geometric reconstruction, 3D semantic segmentation, and 3D instance segmentation into the task of panoptic 3D scene reconstruction - from a single RGB image, predicting the complete geometric reconstruction of the scene in the camera frustum of the image, along with semantic and instance segmentations.
1 code implementation • ICCV 2019 • Manuel Dahnert, Angela Dai, Leonidas Guibas, Matthias Nießner
We propose a novel approach to learn a joint embedding space between scan and CAD geometry, where semantically similar objects from both domains lie close together.
2 code implementations • CVPR 2019 • Armen Avetisyan, Manuel Dahnert, Angela Dai, Manolis Savva, Angel X. Chang, Matthias Nießner
For a 3D reconstruction of an indoor scene, our method takes as input a set of CAD models, and predicts a 9DoF pose that aligns each model to the underlying scan geometry.
Ranked #1 on 3D Reconstruction on Scan2CAD