Objective One of the primary and most appealing goals of computer vision is to automatically understand the content of images on a cognitive level. Ultimately we want to have computers interpret images as we humans do, recognizing all the objects, scenes, and people as well as their relations as they appear in natural images or video. With this project, I want to advance the state of the art in this field in two directions, which I believe to be crucial to build the next generation of image understanding tools. First, novel more robust yet descriptive image representations will be designed, that incorporate the intrinsic structure of images. These should already go a long way towards removing irrelevant sources of variability while capturing the essence of the image content. I believe the importance of further research into image representations is currently underestimated within the research community, yet I claim this is a crucial step with lots of opportunities good learning cannot easily make up for bad features. Second, weakly supervised methods to learn from multimodal input (especially the combination of images and text) will be investigated, making it possible to leverage the large amount of weak annotations available via the internet. This is essential if we want to scale the methods to a larger number of object categories (several hundreds instead of a few tens). As more data can be used for training, such weakly supervised methods might in the end even come on par with or outperform supervised schemes. Here we will call upon the latest results in semi-supervised learning, datamining, and computational linguistics. Fields of science humanitieslanguages and literaturelinguisticsnatural sciencescomputer and information sciencesinternetnatural sciencescomputer and information sciencesartificial intelligencecomputer vision Programme(s) FP7-IDEAS-ERC - Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) Topic(s) ERC-SG-PE6 - ERC Starting Grant - Computer science and informatics Call for proposal ERC-2009-StG See other projects for this call Funding Scheme ERC-SG - ERC Starting Grant Host institution KATHOLIEKE UNIVERSITEIT LEUVEN EU contribution € 1 538 380,00 Address OUDE MARKT 13 3000 Leuven Belgium See on map Region Vlaams Gewest Prov. Vlaams-Brabant Arr. Leuven Activity type Higher or Secondary Education Establishments Administrative Contact Stijn Delauré (Dr.) Principal investigator Tinne Tuytelaars (Prof.) Links Contact the organisation Opens in new window Website Opens in new window Total cost No data Beneficiaries (1) Sort alphabetically Sort by EU Contribution Expand all Collapse all KATHOLIEKE UNIVERSITEIT LEUVEN Belgium EU contribution € 1 538 380,00 Address OUDE MARKT 13 3000 Leuven See on map Region Vlaams Gewest Prov. Vlaams-Brabant Arr. Leuven Activity type Higher or Secondary Education Establishments Administrative Contact Stijn Delauré (Dr.) Principal investigator Tinne Tuytelaars (Prof.) Links Contact the organisation Opens in new window Website Opens in new window Total cost No data
