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Mohamed Nabail

2 accepted papers

2021

BuildingNet: Learning To Label 3D Buildings

ICCV 2021poster

We introduce BuildingNet: (a) a large-scale dataset of 3D building models whose exteriors are consistently labeled, and (b) a graph neural network that labels building meshes by analyzing spatial and structural relations of their geometric primitives. To create our dataset, we used crowdsourcing com…

Cited by 49PDF ↗code ↗Scholar ↗
2020

Neural Contours: Learning to Draw Lines From 3D Shapes

CVPR 2020poster

This paper introduces a method for learning to generate line drawings from 3D models. Our architecture incorporates a differentiable module operating on geometric features of the 3D model, and an image-based module operating on view-based shape representations. At test time, geometric and view-based…

Cited by 44PDF ↗code ↗Scholar ↗