Opendata, web and dolomites

SEED SIGNED

Learning to See in a Dynamic World

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 SEED project word cloud

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

personal    spatial    consolidating    robotics    geometrical    components    segmentation    figure    scene    video    precise    learning    extract    continuous    first    supervision    forecasting    contextual    interact    corresponding    environmental    training    layout    computers    animals    vision    actions    descriptions    assistance    indexing    semantic    accurate    integrating    categories    spaces    observers    reasoning    models    time    perspective    envisaged    temporal    minimal    urban    world    fundamentally    diverse    methodology    scenes    demonstrators    localize    compositional    sense    human    animate    manner    inverse    dynamic    office    propagating    automatic    cars    objects    data    tractable    purpose    seed    machine    chairs    computer    adaptively    boundaries    forecast    techniques    outdoor    acquired    visual    bicycles    editing    manufacturing    supervised    move    indoor    people    ended    interactions    interaction    physical    automatically    ground    phones    qualitative    augmented    recover    acquire    horizons    environments   

Project "SEED" data sheet

The following table provides information about the project.

Coordinator
LUNDS UNIVERSITET 

Organization address
address: Paradisgatan 5c
city: LUND
postcode: 22100
website: n.a.

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 Sweden [SE]
 Project website http://www.maths.lth.se/sminchisescu/
 Total cost 1˙999˙412 €
 EC max contribution 1˙999˙412 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2014-CoG
 Funding Scheme ERC-COG
 Starting year 2016
 Duration (year-month-day) from 2016-01-01   to  2020-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    LUNDS UNIVERSITET SE (LUND) coordinator 1˙999˙412.00

Map

 Project objective

The goal of SEED is to fundamentally advance the methodology of computer vision by exploiting a dynamic analysis perspective in order to acquire accurate, yet tractable models, that can automatically learn to sense our visual world, localize still and animate objects (e.g. chairs, phones, computers, bicycles or cars, people and animals), actions and interactions, as well as qualitative geometrical and physical scene properties, by propagating and consolidating temporal information, with minimal system training and supervision. SEED will extract descriptions that identify the precise boundaries and spatial layout of the different scene components, and the manner they move, interact, and change over time. For this purpose, SEED will develop novel high-order compositional methodologies for the semantic segmentation of video data acquired by observers of dynamic scenes, by adaptively integrating figure-ground reasoning based on bottom-up and top-down information, and by using weakly supervised machine learning techniques that support continuous learning towards an open-ended number of visual categories. The system will be able not only to recover detailed models of dynamic scenes, but also forecast future actions and interactions in those scenes, over long time horizons, by contextual reasoning and inverse reinforcement learning. Two demonstrators are envisaged, the first corresponding to scene understanding and forecasting in indoor office spaces, and the second for urban outdoor environments. The methodology emerging from this research has the potential to impact fields as diverse as automatic personal assistance for people, video editing and indexing, robotics, environmental awareness, augmented reality, human-computer interaction, or manufacturing.

 Publications

year authors and title journal last update
List of publications.
2018 A. Zanfir, C. Sminchisescu
Deep Learning of Graph Matching
published pages: , ISSN: , DOI:
IEEE International Conference on Computer Vision and Pattern Recognition 2019-06-06
2018 H. Petzka and C. Sminchisescu
Non-attracting regions of local minima in deep and wide neural networks
published pages: , ISSN: , DOI:
2019-06-06
2018 M. Zanfir, A.I. Popa, A. Zanfir, C. Sminchisescu
Human Appearance Transfer
published pages: , ISSN: , DOI:
IEEE International Conference on Computer Vision and Pattern Recognition 2019-06-06
2018 A. Pirinen, C. Sminchisescu
Deep Reinforcement Learning of Region Proposal Networks for Object Detection
published pages: , ISSN: , DOI:
IEEE International Conference on Computer Vision and Pattern Rewcognition 2019-06-06
2018 E. Marinoiu, M. Zanfir, V. Olaru, C. Sminchisescu
3D Human Sensing, Action and Emotion Recognition in Robot Assisted Therapy of Children With Autism
published pages: , ISSN: , DOI:
IEEE International Conference on Computer Vision and Pattern Recognition 2019-06-06
2016 D. Nilsson, C. Sminchisescu
Semantic Video Segmentation by Gated Recurrent Flow Propagation
published pages: , ISSN: , DOI:
IEEE International Conference on Computer Vision and Pattern Recognition 2019-06-06
2016 S. Mathe, A. Pirinen, C. Sminchisescu.
Reinforcement Learning for Visual Object Detection
published pages: , ISSN: , DOI:
IEEE International Conference on Computer Vision and Pattern Recognition 2019-06-06
2017 A. Popa, M. Zanfir, C. Sminchisescu
Deep Multitask Architecture for Integrated 2D and 3D Human Sensing
published pages: , ISSN: , DOI:
IEEE International Conference on Computer Vision and Pattern Recognition 2019-06-06
2017 C. Ionescu, A. Popa, C. Sminchisescu
Large-Scale Data Driven Kernel Approximation
published pages: , ISSN: , DOI:
Artificial Intelligence and Statistics 2019-06-06

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "SEED" 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 (fabio@fabiodisconzi.com) 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 "SEED" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.1.1.)

SuperH (2019)

Discovery and Characterization of Hydrogen-Based High-Temperature Superconductors

Read More  

PROGRESS (2019)

The Enemy of the Good: Towards a Theory of Moral Progress

Read More  

SUBMODULAR (2019)

The Power of Randomness and Continuity in Submodular Optimization

Read More