526 citations · 1.4k across the 51 of their papers we have counts for
4 papers · 1 filter
3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans
Ji Hou, Angela Dai, Matthias Nießner
We introduce 3D-SIS, a novel neural network architecture for 3D semantic instance segmentation in commodity RGB-D scans. The core idea of our method is to jointly learn from both g…
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…
Scan2Mesh: From Unstructured Range Scans to 3D Meshes
Angela Dai, Matthias Nießner
We introduce Scan2Mesh, a novel data-driven generative approach which transforms an unstructured and potentially incomplete range scan into a structured 3D mesh representation. The…
3DMV: Joint 3D-Multi-View Prediction for 3D Semantic Scene Segmentation
Angela Dai, Matthias Nießner
We present 3DMV, a novel method for 3D semantic scene segmentation of RGB-D scans in indoor environments using a joint 3D-multi-view prediction network. In contrast to existing met…