CAD-Deform: Deformable Fitting of CAD Models to 3D Scans

Vladislav Ishimtsev1Alexey Bokhovkin1Alexey Artemov1Savva Ignatyev1Matthias Nießner2Denis Zorin3, 1Evgeny Burnaev1

1Skolkovo Institute of Science and Technology2Technical University of Munich3New York University

European Conference on Computer Vision 2020

CAD-Deform takes as input a set of 3D CAD models aligned on a RGB-D scan (left). In order to achieve tight fits (middle), we propose a novel part-based deformation formulation that maintains the desired CAD properties such as sharp features.

Abstract

Shape retrieval and alignment are a promising avenue towards turning 3D scans into lightweight CAD representations that can be used for content creation such as mobile or AR/VR gaming scenarios. Unfortunately, CAD model retrieval is limited by the availability of models in standard 3D shape collections (e.g., ShapeNet). In this work, we address this shortcoming by introducing CAD-Deform, a method which obtains more accurate CAD-to-scan fits by non-rigidly deforming retrieved CAD models. Our key contribution is a new non-rigid deformation model incorporating smooth transformations and preservation of sharp features, that simultaneously achieves very tight fits from CAD models to the 3D scan and maintains the clean, high-quality surface properties of hand-modeled CAD objects. A series of thorough experiments demonstrate that our method achieves significantly tighter scan-to-CAD fits, allowing a more accurate digital replica of the scanned real-world environment while preserving important geometric features present in synthetic CAD environments.

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If you have any questions about this work, please contact us under adase-3ddl@skoltech.ru.