Explore the words cloud of the D3 project. It provides you a very rough idea of what is the project "D3" about.
The following table provides information about the project.
INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE
|Coordinator Country||France [FR]|
|Total cost||1˙482˙761 €|
|EC max contribution||1˙482˙761 € (100%)|
1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
|Duration (year-month-day)||from 2017-02-01 to 2022-01-31|
Take a look of project's partnership.
|1||INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE||FR (LE CHESNAY CEDEX)||coordinator||1˙482˙761.00|
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.
|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.
|year||authors and title||journal||last update|
Yulia Gryaditskaya, Mark Sypesteyn, Jan Willem Hoftijzer, Sylvia Pont, FrÃ©do Durand, Adrien Bousseau
published pages: 1-16, ISSN: 0730-0301, DOI: 10.1145/3355089.3356533
|ACM Transactions on Graphics (TOG) 38/6||2020-03-05|
G. Nishida, A. Bousseau, D. G. Aliaga
Multiâ€Pose Interactive Linkage Design
published pages: 277-289, ISSN: 0167-7055, DOI: 10.1111/cgf.13637
|Computer Graphics Forum 38/2||2019-08-30|
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|
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|
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|
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|
AmÃ©lie 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|
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|
Are you the coordinator (or a participant) of this project? Plaese send me more information about the "D3" project.
For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.
Send me an email (firstname.lastname@example.org) and I put them in your project's page as son as possible.
Thanks. And then put a link of this page into your project's website.
The information about "D3" are provided by the European Opendata Portal: CORDIS opendata.