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Author |
Andres Mafla; Sounak Dey; Ali Furkan Biten; Lluis Gomez; Dimosthenis Karatzas |
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Title |
Multi-modal reasoning graph for scene-text based fine-grained image classification and retrieval |
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Conference Article |
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Year |
2021 |
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IEEE Winter Conference on Applications of Computer Vision |
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4022-4032 |
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Virtual; January 2021 |
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WACV |
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DAG; 600.121 |
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Call Number |
Admin @ si @ MDB2021 |
Serial |
3491 |
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Author |
Andres Mafla; Rafael S. Rezende; Lluis Gomez; Diana Larlus; Dimosthenis Karatzas |
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Title |
StacMR: Scene-Text Aware Cross-Modal Retrieval |
Type |
Conference Article |
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Year |
2021 |
Publication |
IEEE Winter Conference on Applications of Computer Vision |
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Pages |
2219-2229 |
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Virtual; January 2021 |
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WACV |
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DAG; 600.121 |
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Call Number |
Admin @ si @ MRG2021a |
Serial |
3492 |
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Author |
Lluis Gomez; Anguelos Nicolaou; Marçal Rusiñol; Dimosthenis Karatzas |
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Title |
12 years of ICDAR Robust Reading Competitions: The evolution of reading systems for unconstrained text understanding |
Type |
Book Chapter |
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Year |
2020 |
Publication |
Visual Text Interpretation – Algorithms and Applications in Scene Understanding and Document Analysis |
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Springer |
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K. Alahari; C.V. Jawahar |
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Series on Advances in Computer Vision and Pattern Recognition |
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DAG; 600.121 |
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no |
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Call Number |
GNR2020 |
Serial |
3494 |
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Author |
Lluis Gomez; Dena Bazazian; Dimosthenis Karatzas |
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Title |
Historical review of scene text detection research |
Type |
Book Chapter |
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Year |
2020 |
Publication |
Visual Text Interpretation – Algorithms and Applications in Scene Understanding and Document Analysis |
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Springer |
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K. Alahari; C.V. Jawahar |
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Series on Advances in Computer Vision and Pattern Recognition |
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DAG; 600.121 |
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no |
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Call Number |
Admin @ si @ GBK2020 |
Serial |
3495 |
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Author |
Jon Almazan; Lluis Gomez; Suman Ghosh; Ernest Valveny; Dimosthenis Karatzas |
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Title |
WATTS: A common representation of word images and strings using embedded attributes for text recognition and retrieval |
Type |
Book Chapter |
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Year |
2020 |
Publication |
Visual Text Interpretation – Algorithms and Applications in Scene Understanding and Document Analysis |
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Springer |
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Analysis”, K. Alahari; C.V. Jawahar |
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Series on Advances in Computer Vision and Pattern Recognition |
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DAG; 600.121 |
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no |
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Call Number |
Admin @ si @ AGG2020 |
Serial |
3496 |
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Author |
Josep Llados |
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Title |
The 5G of Document Intelligence |
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Conference Article |
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Year |
2021 |
Publication |
3rd Workshop on Future of Document Analysis and Recognition |
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Lausanne; Suissa; September 2021 |
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FDAR |
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DAG |
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no |
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Call Number |
Admin @ si @ |
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3677 |
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Author |
Utkarsh Porwal; Alicia Fornes; Faisal Shafait (eds) |
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Title |
Frontiers in Handwriting Recognition. International Conference on Frontiers in Handwriting Recognition. 18th International Conference, ICFHR 2022 |
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Book Whole |
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Year |
2022 |
Publication |
Frontiers in Handwriting Recognition. |
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Volume |
13639 |
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ICFHR 2022, Hyderabad, India, December 4–7, 2022 |
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Springer |
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Utkarsh Porwal; Alicia Fornes; Faisal Shafait |
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LNCS |
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978-3-031-21648-0 |
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ICFHR |
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DAG |
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no |
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Admin @ si @ PFS2022 |
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3809 |
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Author |
Mickael Coustaty; Alicia Fornes |
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Title |
Document Analysis and Recognition – ICDAR 2023 Workshops |
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Book Whole |
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Year |
2023 |
Publication |
Document Analysis and Recognition – ICDAR 2023 Workshops |
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Volume |
14194 |
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2 |
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Address |
San Jose; USA; August 2023 |
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Conference |
ICDAR |
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DAG |
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no |
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Call Number |
Admin @ si @ CoF2023 |
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3852 |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Text line extraction in graphical documents using background and foreground |
Type |
Journal Article |
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Year |
2012 |
Publication |
International Journal on Document Analysis and Recognition |
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IJDAR |
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Volume |
15 |
Issue |
3 |
Pages |
227-241 |
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Abstract |
0,405 JCR
In graphical documents (e.g., maps, engineering drawings), artistic documents etc., the text lines are annotated in multiple orientations or curvilinear way to illustrate different locations or symbols. For the optical character recognition of such documents, individual text lines from the documents need to be extracted. In this paper, we propose a novel method to segment such text lines and the method is based on the foreground and background information of the text components. To effectively utilize the background information, a water reservoir concept is used here. In the proposed scheme, at first, individual components are detected and grouped into character clusters in a hierarchical way using size and positional information. Next, the clusters are extended in two extreme sides to determine potential candidate regions. Finally, with the help of these candidate regions,
individual lines are extracted. The experimental results are presented on different datasets of graphical documents, camera-based warped documents, noisy images containing seals, etc. The results demonstrate that our approach is robust and invariant to size and orientation of the text lines present in
the document. |
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1433-2833 |
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DAG |
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no |
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Call Number |
Admin @ si @ RPL2012b |
Serial |
2134 |
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Author |
Alicia Fornes; Anjan Dutta; Albert Gordo; Josep Llados |
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Title |
CVC-MUSCIMA: A Ground-Truth of Handwritten Music Score Images for Writer Identification and Staff Removal |
Type |
Journal Article |
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Year |
2012 |
Publication |
International Journal on Document Analysis and Recognition |
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IJDAR |
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15 |
Issue |
3 |
Pages |
243-251 |
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Keywords |
Music scores; Handwritten documents; Writer identification; Staff removal; Performance evaluation; Graphics recognition; Ground truths |
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Abstract |
0,405JCR
The analysis of music scores has been an active research field in the last decades. However, there are no publicly available databases of handwritten music scores for the research community. In this paper we present the CVC-MUSCIMA database and ground-truth of handwritten music score images. The dataset consists of 1,000 music sheets written by 50 different musicians. It has been especially designed for writer identification and staff removal tasks. In addition to the description of the dataset, ground-truth, partitioning and evaluation metrics, we also provide some base-line results for easing the comparison between different approaches. |
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1433-2833 |
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DAG |
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Call Number |
Admin @ si @ FDG2012 |
Serial |
2129 |
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