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D3 SIGNED

Interpreting Drawings for 3D Design

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 D3 project word cloud

Explore the words cloud of the D3 project. It provides you a very rough idea of what is the project "D3" about.

feasibility    technique    shapes    geometric    understand    cast    solutions    train    data    creative    drawings    indicating    idea    algorithms    automatically    techniques    exploration    draw    point    ill    rigidity    finalized    nature    computer    3d    model    tediousness    constraints    originality    clashes    single    input    first    create    anywhere    learning    impractical    synthetic    models    feedback    professional    rapid    modeling    drawing    designers    power    inverse    prototyping    satisfies    tools    extensively    interpretable    tighten    visceral    communicate    printing    tackling    significantly    reconstruction    shape    synthesize    formalize    ideas    viewers    constraint    joint    interpret    simulation    machine    physical    computers    image    estimating    posed    derive    approximate    limited    suitable    optimization    provides    externalize    continuous    ambition    representing    variables    engineering    configurations    lie    discrete    leverage    predict   

Project "D3" data sheet

The following table provides information about the project.

Coordinator
INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE 

Organization address
address: DOMAINE DE VOLUCEAU ROCQUENCOURT
city: LE CHESNAY CEDEX
postcode: 78153
website: www.inria.fr

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country France [FR]
 Total cost 1˙482˙761 €
 EC max contribution 1˙482˙761 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2016-STG
 Funding Scheme ERC-STG
 Starting year 2017
 Duration (year-month-day) from 2017-02-01   to  2022-01-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE FR (LE CHESNAY CEDEX) coordinator 1˙482˙761.00

Map

 Project objective

Designers draw extensively to externalize their ideas and communicate with others. However, drawings are currently not directly interpretable by computers. To test their ideas against physical reality, designers have to create 3D models suitable for simulation and 3D printing. However, the visceral and approximate nature of drawing clashes with the tediousness and rigidity of 3D modeling. As a result, designers only model finalized concepts, and have no feedback on feasibility during creative exploration. Our ambition is to bring the power of 3D engineering tools to the creative phase of design by automatically estimating 3D models from drawings. However, this problem is ill-posed: a point in the drawing can lie anywhere in depth. Existing solutions are limited to simple shapes, or require user input to “explain” to the computer how to interpret the drawing. Our originality is to exploit professional drawing techniques that designers developed to communicate shape most efficiently. Each technique provides geometric constraints that help viewers understand drawings, and that we shall leverage for 3D reconstruction. Our first challenge is to formalize common drawing techniques and derive how they constrain 3D shape. Our second challenge is to identify which techniques are used in a drawing. We cast this problem as the joint optimization of discrete variables indicating which constraints apply, and continuous variables representing the 3D model that best satisfies these constraints. But evaluating all constraint configurations is impractical. To solve this inverse problem, we will first develop forward algorithms that synthesize drawings from 3D models. Our idea is to use this synthetic data to train machine learning algorithms that predict the likelihood that constraints apply in a given drawing. In addition to tackling the long-standing problem of single-image 3D reconstruction, our research will significantly tighten design and engineering for rapid prototyping.

 Deliverables

List of deliverables.
Data Management Plan Open Research Data Pilot 2019-05-31 11:58:51

Take a look to the deliverables list in detail:  detailed list of D3 deliverables.

 Publications

year authors and title journal last update
List of publications.
2019 Yulia Gryaditskaya, Mark Sypesteyn, Jan Willem Hoftijzer, Sylvia Pont, Frédo Durand, Adrien Bousseau
OpenSketch
published pages: 1-16, ISSN: 0730-0301, DOI: 10.1145/3355089.3356533
ACM Transactions on Graphics (TOG) 38/6 2020-03-05
2019 G. Nishida, A. Bousseau, D. G. Aliaga
Multi‐Pose Interactive Linkage Design
published pages: 277-289, ISSN: 0167-7055, DOI: 10.1111/cgf.13637
Computer Graphics Forum 38/2 2019-08-30
2019 Jean-Dominique Favreau, Florent Lafarge, Adrien Bousseau, Alex Auvolat
Extracting Geometric Structures in Images with Delaunay Point Processes
published pages: 1-1, ISSN: 0162-8828, DOI: 10.1109/tpami.2018.2890586
IEEE Transactions on Pattern Analysis and Machine Intelligence 2019-08-30
2019 Johanna Delanoy, David Coeurjolly, Jacques-Olivier Lachaud, Adrien Bousseau
Combining voxel and normal predictions for multi-view 3D sketching
published pages: 65-72, ISSN: 0097-8493, DOI: 10.1016/j.cag.2019.05.024
Computers & Graphics 82 2019-08-30
2018 Johanna Delanoy, Mathieu Aubry, Phillip Isola, Alexei A. Efros, Adrien Bousseau
3D Sketching using Multi-View Deep Volumetric Prediction
published pages: 1-22, ISSN: 2577-6193, DOI: 10.1145/3203197
Proceedings of the ACM on Computer Graphics and Interactive Techniques 1/1 2019-06-13
2018 Gen Nishida, Adrien Bousseau, Daniel G. Aliaga
Procedural Modeling of a Building from a Single Image
published pages: 415-429, ISSN: 0167-7055, DOI: 10.1111/cgf.13372
Computer Graphics Forum 37/2 2019-06-13
2017 Amélie Fondevilla, Adrien Bousseau, Damien Rohmer, Stefanie Hahmann, Marie-Paule Cani
Patterns from photograph: Reverse-engineering developable products
published pages: 4-13, ISSN: 0097-8493, DOI: 10.1016/j.cag.2017.05.017
Computers & Graphics 66 2019-06-13
2017 Favreau , Jean-Dominique; Lafarge , Florent; Bousseau , Adrien ,
Photo2ClipArt: Image Abstraction and Vectorization Using Layered Linear Gradients
published pages: , ISSN: 0730-0301, DOI: 10.1145/3130800.3130888
ACM Transactions on Graphics 6 2019-06-13

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The information about "D3" are provided by the European Opendata Portal: CORDIS opendata.

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