Scan2CAD: Learning CAD Model Alignment in RGB-D Scans

CVPR 2019 Armen AvetisyanManuel DahnertAngela DaiManolis SavvaAngel X. ChangMatthias Nießner

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 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... (read more)

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Evaluation results from the paper

Task Dataset Model Metric name Metric value Global rank Compare
3D Reconstruction Scan2CAD Scan2CAD Average Accuracy 31.68% # 1