CORDIS
EU research results

CORDIS

English EN

Learning Generative 3D Scene Models for Training and Validating Intelligent Systems

Objective

Recently, the field of computer vision has witnessed a major transformation away from expert designed shallow models towards more generic deep representation learning. However, collecting labeled data for training deep models is costly and existing simulators with artist-designed scenes do not provide the required variety and fidelity. Project LEGO-3D will tackle this problem by developing probabilistic models capable of synthesizing 3D scenes jointly with photo-realistic 2D projections from arbitrary viewpoints and with full control over the scene elements. Our key insight is that data augmentation, while hard in 2D, becomes considerably easier in 3D as physical properties such as viewpoint invariances and occlusion relationships are captured by construction. Thus, our goal is to learn the entire 3D-to-2D simulation pipeline. In particular, we will focus on the following problems:

(A) We will devise algorithms for automatic decomposition of real and synthetic scenes into latent 3D primitive representations capturing geometry, material, light and motion.

(B) We will develop novel probabilistic generative models which are able to synthesize large-scale 3D environments based on the primitives extracted in project (A). In particular, we will develop unconditional, conditioned and spatio-temporal scene generation networks.

(C) We will combine differentiable and neural rendering techniques with deep learning based image synthesis, yielding high-fidelity 2D renderings of the 3D representations generated in project (B) while capturing ambiguities and uncertainties.

Project LEGO-3D will significantly impact a large number of application areas. Examples include vision systems which require access to large amounts of annotated data, safety-critical applications such as autonomous cars that rely on efficient ways for training and validation, as well as the entertainment industry which seeks to automate the creation and manipulation of 3D content.
Leaflet | Map data © OpenStreetMap contributors, Credit: EC-GISCO, © EuroGeographics for the administrative boundaries

Host institution

EBERHARD KARLS UNIVERSITAET TUEBINGEN

Address

Geschwister-Scholl-Platz
72074 Tuebingen

Germany

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 1 467 500

Beneficiaries (1)

Sort alphabetically

Sort by EU Contribution

Expand all

EBERHARD KARLS UNIVERSITAET TUEBINGEN

Germany

EU Contribution

€ 1 467 500

Project information

Grant agreement ID: 850533

Status

Grant agreement signed

  • Start date

    1 October 2020

  • End date

    30 September 2025

Funded under:

H2020-EU.1.1.

  • Overall budget:

    € 1 467 500

  • EU contribution

    € 1 467 500

Hosted by:

EBERHARD KARLS UNIVERSITAET TUEBINGEN

Germany