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Author |
Josep Brugues Pujolras; Lluis Gomez; Dimosthenis Karatzas |
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Title ![sorted by Title field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
A Multilingual Approach to Scene Text Visual Question Answering |
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Conference Article |
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2022 |
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Document Analysis Systems.15th IAPR International Workshop, (DAS2022) |
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65-79 |
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Scene text; Visual question answering; Multilingual word embeddings; Vision and language; Deep learning |
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Scene Text Visual Question Answering (ST-VQA) has recently emerged as a hot research topic in Computer Vision. Current ST-VQA models have a big potential for many types of applications but lack the ability to perform well on more than one language at a time due to the lack of multilingual data, as well as the use of monolingual word embeddings for training. In this work, we explore the possibility to obtain bilingual and multilingual VQA models. In that regard, we use an already established VQA model that uses monolingual word embeddings as part of its pipeline and substitute them by FastText and BPEmb multilingual word embeddings that have been aligned to English. Our experiments demonstrate that it is possible to obtain bilingual and multilingual VQA models with a minimal loss in performance in languages not used during training, as well as a multilingual model trained in multiple languages that match the performance of the respective monolingual baselines. |
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La Rochelle, France; May 22–25, 2022 |
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DAS |
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DAG; 611.004; 600.155; 601.002 |
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Admin @ si @ BGK2022b |
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3695 |
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Author |
Josep Llados; Felipe Lumbreras; Javier Varona |
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Title ![sorted by Title field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
A multidocument platform for automatic reading of identity cards. |
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Miscellaneous |
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1999 |
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Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Analisis de Imagenes. |
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Bilbao |
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ADAS;DAG |
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ADAS @ adas @ LLV1999 |
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7 |
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Author |
Agnes Borras; Josep Llados |
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Title ![sorted by Title field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
A Multi-Scale Layout Descriptor Based on Delaunay Triangulation for Image Retrieval |
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2008 |
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3rd International Conference on Computer Vision Theory and Applications VISAPP (2) 2008 |
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2 |
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139-144 |
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Funchal, Madeira (Portugal) |
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DAG |
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DAG @ dag @ BoL2008 |
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981 |
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Author |
Marçal Rusiñol |
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Title ![sorted by Title field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
A Model of Vectorial Signatures in Terms of Expressive Sub-Shapes: Symbol Indexation in Technical Documents |
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2006 |
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CVC Technical Report #94 |
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CVC (UAB) |
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DAG |
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DAG @ dag @ Rus2006 |
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668 |
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Author |
Ernest Valveny; Enric Marti |
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Title ![sorted by Title field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
A model for image generation and symbol recognition through the deformation of lineal shapes |
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2003 |
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Pattern Recognition Letters |
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PRL |
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24 |
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15 |
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2857-2867 |
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We describe a general framework for the recognition of distorted images of lineal shapes, which relies on three items: a model to represent lineal shapes and their deformations, a model for the generation of distorted binary images and the combination of both models in a common probabilistic framework, where the generation of deformations is related to an internal energy, and the generation of binary images to an external energy. Then, recognition consists in the minimization of a global energy function, performed by using the EM algorithm. This general framework has been applied to the recognition of hand-drawn lineal symbols in graphic documents. |
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Elsevier Science Inc. |
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New York, NY, USA |
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0167-8655 |
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DAG; IAM |
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IAM @ iam @ VAM2003 |
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1653 |
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Author |
Gemma Sanchez; Josep Llados; K. Tombre |
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Title ![sorted by Title field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
A mean string algorithm to compute the average among a set of 2D shapes |
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2002 |
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Pattern Recognition Letters |
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PRL |
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23 |
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1-3 |
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203–214 |
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DAG; IF: 0.409 |
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DAG @ dag @ SLT2002 |
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275 |
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Author |
Gemma Sanchez; Josep Llados; K. Tombre |
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Title ![sorted by Title field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
A mean string algorithm to compute the average among a set of 2D shapes |
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2000 |
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CVC Technical Report #38 |
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CVC (UAB) |
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DAG |
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DAG @ dag @ SLT2000 |
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350 |
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Author |
Fernando Vilariño; Dimosthenis Karatzas |
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Title ![sorted by Title field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
A Living Lab approach for Citizen Science in Libraries |
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Conference Article |
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2016 |
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1st International ECSA Conference |
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Berlin; Germany; May 2016 |
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ECSA |
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MV; DAG; 600.084; 600.097;SIAI |
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Admin @ si @ViK2016 |
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2804 |
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Author |
Alicia Fornes; Volkmar Frinken; Andreas Fischer; Jon Almazan; G. Jackson; Horst Bunke |
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Title ![sorted by Title field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
A Keyword Spotting Approach Using Blurred Shape Model-Based Descriptors |
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Conference Article |
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2011 |
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Proceedings of the 2011 Workshop on Historical Document Imaging and Processing |
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83-90 |
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The automatic processing of handwritten historical documents is considered a hard problem in pattern recognition. In addition to the challenges given by modern handwritten data, a lack of training data as well as effects caused by the degradation of documents can be observed. In this scenario, keyword spotting arises to be a viable solution to make documents amenable for searching and browsing. For this task we propose the adaptation of shape descriptors used in symbol recognition. By treating each word image as a shape, it can be represented using the Blurred Shape Model and the De-formable Blurred Shape Model. Experiments on the George Washington database demonstrate that this approach is able to outperform the commonly used Dynamic Time Warping approach. |
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ACM |
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978-1-4503-0916-5 |
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HIP |
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DAG |
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Admin @ si @ FFF2011a |
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1823 |
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Author |
Albert Gordo; Jaume Gibert; Ernest Valveny; Marçal Rusiñol |
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Title ![sorted by Title field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
A Kernel-based Approach to Document Retrieval |
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Conference Article |
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2010 |
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9th IAPR International Workshop on Document Analysis Systems |
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377–384 |
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In this paper we tackle the problem of document image retrieval by combining a similarity measure between documents and the probability that a given document belongs to a certain class. The membership probability to a specific class is computed using Support Vector Machines in conjunction with similarity measure based kernel applied to structural document representations. In the presented experiments, we use different document representations, both visual and structural, and we apply them to a database of historical documents. We show how our method based on similarity kernels outperforms the usual distance-based retrieval. |
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Boston; USA; |
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978-1-60558-773-8 |
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DAG @ dag @ GGV2010 |
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1431 |
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