Towards Part-Based Understanding of RGB-D Scans
part-based-scan-understanding
Towards Part-Based Understanding of RGB-D Scans (CVPR 2021)
We propose the task of part-based scene understanding of real-world 3D environments: from an RGB-D scan of a scene, we detect objects, and for each object predict its decomposition into geometric part masks, which composed together form the complete geometry of the observed object.
Demo samples
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The core of this repository is a network, which takes as input preprocessed scan voxel crops and produces voxelized part trees.
However, data preparation is very massive step before launching actual training and inference. That’s why we release already prepared
data for training and checkpoint to perform inference.
If you want to launch training with our data, please follow the steps below: