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Found 3 papers, 1 papers with code
Fully-Convolutional Point Networks for Large-Scale Point Clouds
This work proposes a general-purpose, fully-convolutional network architecture for efficiently processing large-scale 3D data.
Ranked #26 on
Semantic Segmentation
on ScanNet
ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans
We introduce ScanComplete, a novel data-driven approach for taking an incomplete 3D scan of a scene as input and predicting a complete 3D model along with per-voxel semantic labels.
De-noising, Stabilizing and Completing 3D Reconstructions On-the-go using Plane Priors
Our implementation is optimized to run in real-time on mobile devices such as the Tango tablet.
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