Papers › Automatically Annotating Indoor Images with CAD Models via RGB-D Scans

Automatically Annotating Indoor Images with CAD Models via RGB-D Scans

22 Dec 2022arXiv:2212.11796archive 2025-07-28

Stefan Ainetter, Sinisa Stekovic, Friedrich Fraundorfer, Vincent Lepetit

We present an automatic method for annotating images of indoor scenes with the CAD models of the objects by relying on RGB-D scans. Through a visual evaluation by 3D experts, we show that our method retrieves annotations that are at least as accurate as manual annotations, and can thus be used as ground truth without the burden of manually annotating 3D data. We do this using an analysis-by-synthesis approach, which compares renderings of the CAD models with the captured scene. We introduce a 'cloning procedure' that identifies objects that have the same geometry, to annotate these objects with the same CAD models. This allows us to obtain complete annotations for the ScanNet dataset and the recent ARKitScenes dataset.

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Code

stefan-ainetter/SCANnotateDataset officialpytorchGPL-3.0 report
stefan-ainetter/scannotate mentioned in papermentioned on GitHubpytorchGPL-3.0 report

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3D Object RetrievalPose EstimationPose Retrieval

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