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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences biological sciences zoology
- natural sciences computer and information sciences artificial intelligence machine learning unsupervised learning
- natural sciences computer and information sciences artificial intelligence computer vision
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
- natural sciences computer and information sciences artificial intelligence computational intelligence
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
ERC-STG - Starting Grant
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2014-STG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
OX1 2JD Oxford
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.