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Author  |
Lluis Gomez; Andres Mafla; Marçal Rusiñol; Dimosthenis Karatzas | ||||
| Title | Single Shot Scene Text Retrieval | Type | Conference Article | ||
| Year | 2018 | Publication | 15th European Conference on Computer Vision | Abbreviated Journal | |
| Volume | 11218 | Issue | Pages | 728-744 | |
| Keywords | Image retrieval; Scene text; Word spotting; Convolutional Neural Networks; Region Proposals Networks; PHOC | ||||
| Abstract | Textual information found in scene images provides high level semantic information about the image and its context and it can be leveraged for better scene understanding. In this paper we address the problem of scene text retrieval: given a text query, the system must return all images containing the queried text. The novelty of the proposed model consists in the usage of a single shot CNN architecture that predicts at the same time bounding boxes and a compact text representation of the words in them. In this way, the text based image retrieval task can be casted as a simple nearest neighbor search of the query text representation over the outputs of the CNN over the entire image
database. Our experiments demonstrate that the proposed architecture outperforms previous state-of-the-art while it offers a significant increase in processing speed. |
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| Address | Munich; September 2018 | ||||
| Corporate Author | Thesis | ||||
| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | ECCV | ||
| Notes | DAG; 600.084; 601.338; 600.121; 600.129 | Approved | no | ||
| Call Number | Admin @ si @ GMR2018 | Serial | 3143 | ||
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