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IDIU SIGNED

Integrated and Detailed Image Understanding

Total Cost €

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EC-Contrib. €

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Partnership

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Project "IDIU" data sheet

The following table provides information about the project.

Coordinator
THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD 

Organization address
address: WELLINGTON SQUARE UNIVERSITY OFFICES
city: OXFORD
postcode: OX1 2JD
website: www.ox.ac.uk

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 United Kingdom [UK]
 Project website http://www.robots.ox.ac.uk/
 Total cost 1˙497˙271 €
 EC max contribution 1˙497˙271 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2014-STG
 Funding Scheme ERC-STG
 Starting year 2015
 Duration (year-month-day) from 2015-08-01   to  2021-07-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD UK (OXFORD) coordinator 1˙497˙271.00

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 Project objective

The aim of this project is to create the technology needed to understand the content of images in a detailed, human-like manner, significantly superseding the current limitations of automatic image understanding, and enabling new far reaching human-centric applications. The first goal is to substantially broaden the spectrum of visual information that machines can extract from images. For example, where current technology may discover that there is a ``person' in an image, we would like to produce a description such as ``person wearing a red uniform, tall, brown haired, with a bayonet, and a long black hat.' The second goal is to do so efficiently, by developing integrated image representations that can share knowledge and computation in multiple computer vision tasks, from detecting edges to recognising and describing thousands of different object types.

In order to do so, we will investigate, for the fist time in a systematic manner, the breadth of information that humans can extract from images, from abstract patterns to object parts and attributes, and we will incorporate it in the next generation of machine vision systems. Compared to existing technology, the new algorithms will have a significantly richer and more detailed understanding of the content of images. They will be learned from data building on recent breakthroughs in large scale discriminative and deep machine learning, and will be delivered as general-purpose open-source software for the benefit of the research community and businesses. In order to make these systems future-proof, we will develop methods to extend them automatically, by learning from images downloaded from the Internet with very little human supervision. These new advanced capabilities will be demonstrated in breakthrough applications in large scale image search and visual information retrieval.

 Publications

year authors and title journal last update
List of publications.
2019 Thomas Jakab, Andrea Vedaldi
Learning Human Pose from Unaligned Data through Image Translation
published pages: , ISSN: , DOI:
2020-02-07
2019 Sebastien Ehrhardt, Aron Monszpart, Niloy J. Mitra, Andrea Vedaldi
Taking visual motion prediction to new heightfields
published pages: 14-25, ISSN: 1077-3142, DOI: 10.1016/j.cviu.2019.02.005
Computer Vision and Image Understanding 181 2020-02-07
2019 X.Ji, J. F. Henriques, A. Vedaldi
Invariant Information Clustering for Unsupervised Image Classification and Segmentation
published pages: 9865-9874, ISSN: , DOI:
IEEE International Conference on Computer Vision, 2019 2020-02-07
2019 Vassileios Balntas, Karel Lenc, Andrea Vedaldi, Tinne Tuytelaars, Jiri Matas, Krystian Mikolajczyk
HPatches: A benchmark and evaluation of handcrafted and learned local descriptors
published pages: 1-1, ISSN: 0162-8828, DOI: 10.1109/tpami.2019.2915233
IEEE Transactions on Pattern Analysis and Machine Intelligence 2020-02-07
2019 HAN K, VEDALDI A, ZISSERMAN A
Learning to Discover Novel Visual Categories via Deep Transfer Clustering
published pages: , ISSN: , DOI:
IEEE ICCV 2019 2020-02-07
2019 Bertinetto L, HENRIQUES J, TORR PHS, VEDALDI A
META-LEARNING WITH DIFFERENTIABLE CLOSED-FORM SOLVERS
published pages: , ISSN: , DOI:
International Conference on Learning Representations (ICLR), 2019 2020-02-07
2016 Aravindh Mahendran, Andrea Vedaldi
Visualizing Deep Convolutional Neural Networks Using Natural Pre-images
published pages: , ISSN: 0920-5691, DOI: 10.1007/s11263-016-0911-8
International Journal of Computer Vision 2020-02-07
2018 J.F. Henriques, A. Vedaldi
MapNet: An Allocentric Spatial memory for Mapping Environments
published pages: , ISSN: , DOI:
IEEE CVPR 2018 2020-02-07
2016 Novotny D, Larlus D, Vedaldi A
Learning the Structure of Objects from Web Supervision
published pages: , ISSN: , DOI: 10.1007/978-3-319-49409-8_19
ECCV Workshop on Geometry Meets Deep Learning 8-16 October 2020-02-07
2018 Karel Lenc, Andrea Vedaldi
Understanding Image Representations by Measuring Their Equivariance and Equivalence
published pages: , ISSN: 0920-5691, DOI: 10.1007/s11263-018-1098-y
International Journal of Computer Vision 2020-02-07
2017 James Thewlis, Hakan Bilen, Andrea Vedaldi
Unsupervised Learning of Object Landmarks by Factorized Spatial Embeddings
published pages: , ISSN: , DOI:
International Conference on Computer Vision (ICCV) 2020-02-07
2017 Henriques, J.F., Vedaldi, A.
Warped convolutions: efficient invariance to spatial transformation
published pages: , ISSN: , DOI:
ICML 7-9 August, 2017 2020-02-07
2016 Luca Bertinetto, Joao Henriques, Jack Valmadre, Philip Torr and Andrea Vedaldi
Learning feed-forward one-shot learners
published pages: , ISSN: , DOI:
Neural Information Processing Systems (NIPS) 5-8 December 2020-02-07
2016 Hakan Bilen, Andrea Vedaldi
Integrated Perception with Recurrent Multi-Task Neural Networks
published pages: , ISSN: , DOI:
Neural Information Processing Systems (NIPS) 2020-02-07
2018 R. Fong, A. Vedaldi
NetVec: Quantifying and explaining how Concepts are Encoded by Filters in Deep Neural Networks
published pages: , ISSN: , DOI:
IEEE CVPR 2018 2020-02-07
2016 Luca Bertinetto, Jack Valmadre, João F. Henriques, Andrea Vedaldi, Philip H. S. Torr
Fully-Convolutional Siamese Networks for Object Tracking
published pages: 850-865, ISSN: , DOI: 10.1007/978-3-319-48881-3_56
ECCV 2016 8-16 October 2016 2020-02-07
2017 Sylvestre-Alvise Rebuffi, Hakan Bilen, Andrea Vedaldi
Learning multiple visual domains with residual adapters
published pages: , ISSN: , DOI:
Neural Information Processing Systems (NIPS) 2020-02-07
2016 Mircea Cimpoi, Subhransu Maji, Iasonas Kokkinos, Andrea Vedaldi
Deep Filter Banks for Texture Recognition, Description, and Segmentation
published pages: 65-94, ISSN: 0920-5691, DOI: 10.1007/s11263-015-0872-3
International Journal of Computer Vision 118/1 2020-02-07
2017 David Novotny, Diane Larlus, Andrea Vedaldi
Learning 3D Object Categories by Looking Around Them
published pages: , ISSN: , DOI:
International Conference on Computer Vision (ICCV) 2020-02-07
2017 James Thewlis, Hakan Bilen, Andrea Vedaldi
Unsupervised learning of object frames by dense equivariant image labelling
published pages: , ISSN: , DOI:
Neural Information Processing Systems (NIPS) 2020-02-07
2016 Aravindh Mahendran, Andrea Vedaldi
Salient Deconvolutional Networks
published pages: 120-135, ISSN: , DOI: 10.1007/978-3-319-46466-4_8
ECCV 8-16 October 2016 2020-02-07
2018 S-A.Rebuffi, H.Bilen, A.Vedaldi
Efficient parametrization of multi-domain biometric matching
published pages: , ISSN: , DOI:
IEEE CVPR 2018 2020-02-07
2016 Karel Lenc, Andrea Vedaldi
Learning Covariant Feature Detectors
published pages: 100-117, ISSN: , DOI: 10.1007/978-3-319-49409-8_11
ECCV Workshop on Geometry Meets Deep Learning 9 October, 2016 2020-02-07
2018 S. Ehrhardt; A. Monszpart; N. Mitra; A. Vedaldi
Unsupervised intuitive physics from visual observations
published pages: , ISSN: , DOI:
ACCV 2018 2020-02-07
2018 R.Fong; A.Vedaldi
Net2Vec: Quantifying and Explaining How Concepts are Encoded by Filters in Deep Neural Networks
published pages: , ISSN: , DOI:
IEEE CVPR2018 2020-02-07
2018 T.Jakab, A.Gupta, H.Bilen, A.Vedaldi
Unsupervised Learning of Object Landmarks through Conditional Image Generation
published pages: , ISSN: , DOI:
2020-02-07
2018 J.Hu, L.Shen, S.Albanie, G.Sum, A.Vedaldi
Gather-Excite: Exploiting Feature Context in Convolutional Neural Networks
published pages: , ISSN: , DOI:
NIPS 2018 2020-02-07
2018 K.Lenc, A.Vedaldi
Large scale evaluation of local image feature detectors on homography datasets
published pages: , ISSN: , DOI:
2020-02-07

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