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ABC Dataset

A Big CAD Model Dataset For Geometric Deep Learning

ABC Dataset

We introduce ABC-Dataset, a collection of one million Computer-Aided Design (CAD) models for research of geometric deep learning methods and applications. Each model is a collection of explicitly parametrized curves and surfaces, providing ground truth for differential quantities, patch segmentation, geometric feature detection, and shape reconstruction. Sampling the parametric descriptions of surfaces and curves allows generating data in different formats and resolutions, enabling fair comparisons for a wide range of geometric learning algorithms. As a use case for our dataset, we perform a large-scale benchmark for estimation of surface normals, comparing existing data driven methods and evaluating their performance against both the ground truth and traditional normal estimation methods.

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Task
3D Reconstruction / Photogrammetry
Annotation Types
Semantic Segmentation
Items
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Models using this dataset
Last updated on 
January 20, 2022
Licensed under 
Research Only
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