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Author |
Ernest Valveny; Enric Marti |
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Title |
Learning of structural descriptions of graphic symbols using deformable template matching |
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2001 |
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Proc. Sixth Int Document Analysis and Recognition Conf |
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455-459 |
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Accurate symbol recognition in graphic documents needs an accurate representation of the symbols to be recognized. If structural approaches are used for recognition, symbols have to be described in terms of their shape, using structural relationships among extracted features. Unlike statistical pattern recognition, in structural methods, symbols are usually manually defined from expertise knowledge, and not automatically infered from sample images. In this work we explain one approach to learn from examples a representative structural description of a symbol, thus providing better information about shape variability. The description of a symbol is based on a probabilistic model. It consists of a set of lines described by the mean and the variance of line parameters, respectively providing information about the model of the symbol, and its shape variability. The representation of each image in the sample set as a set of lines is achieved using deformable template matching. |
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DAG;IAM; |
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IAM @ iam @ VMA2001 |
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1654 |
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Author |
Maria Vanrell; Felipe Lumbreras; A. Pujol; Ramon Baldrich; Josep Llados; Juan J. Villanueva |
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Title |
Colour Normalisation Based on Background Information. |
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Miscellaneous |
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2001 |
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Proceeding ICIP 2001, IEEE International Conference on Image Processing |
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ICIP 2001 |
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1 |
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874–877 |
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Grecia. |
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ADAS;DAG;CIC |
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ADAS @ adas @ VLP2001 |
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167 |
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Author |
Josep Llados; Enric Marti; Jaime Lopez-Krahe |
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Title |
A Hough-based method for hatched pattern detection in maps and diagrams |
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1999 |
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Proceeding of the Fifth Int. Conf. Document Analysis and Recognition ICDAR ’99 |
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479-482 |
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A hatched area is characterized by a set of parallel straight lines placed at regular intervals. In this paper, a Hough-based schema is introduced to recognize hatched areas in technical documents from attributed graph structures representing the document once it has been vectorized. Defining a Hough-based transform from a graph instead of the raster image allows to drastically reduce the processing time and, second, to obtain more reliable results because straight lines have already been detected in the vectorization step. A second advantage of the proposed method is that no assumptions must be made a priori about the slope and frequency of hatching patterns, but they are computed in run time for each hatched area. |
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DAG;IAM; |
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IAM @ iam @ LIM1999b |
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1580 |
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Author |
Ernest Valveny; Ricardo Toledo; Ramon Baldrich; Enric Marti |
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Combining recognition-based in segmentation-based approaches for graphic symol recognition using deformable template matching |
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2002 |
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Proceeding of the Second IASTED International Conference Visualization, Imaging and Image Proceesing VIIP 2002 |
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502–507 |
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DAG;RV;CAT;IAM;CIC;ADAS |
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IAM @ iam @ VTB2002 |
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1660 |
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Ramon Baldrich; Ricardo Toledo; Ernest Valveny; Maria Vanrell |
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Title |
Perceptual Colour Image Segmentation. |
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2002 |
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Proceeding of the Second IASTED International Conference Visualization, Imaging and Image Proceesing VIIP 2002: 145–150. |
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DAG;CIC;ADAS |
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CAT @ cat @ BTV2002 |
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290 |
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Author |
Emanuele Vivoli; Ali Furkan Biten; Andres Mafla; Dimosthenis Karatzas; Lluis Gomez |
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Title |
MUST-VQA: MUltilingual Scene-text VQA |
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Conference Article |
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2022 |
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Proceedings European Conference on Computer Vision Workshops |
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13804 |
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345–358 |
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Visual question answering; Scene text; Translation robustness; Multilingual models; Zero-shot transfer; Power of language models |
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In this paper, we present a framework for Multilingual Scene Text Visual Question Answering that deals with new languages in a zero-shot fashion. Specifically, we consider the task of Scene Text Visual Question Answering (STVQA) in which the question can be asked in different languages and it is not necessarily aligned to the scene text language. Thus, we first introduce a natural step towards a more generalized version of STVQA: MUST-VQA. Accounting for this, we discuss two evaluation scenarios in the constrained setting, namely IID and zero-shot and we demonstrate that the models can perform on a par on a zero-shot setting. We further provide extensive experimentation and show the effectiveness of adapting multilingual language models into STVQA tasks. |
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Tel-Aviv; Israel; October 2022 |
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ECCVW |
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DAG; 302.105; 600.155; 611.002 |
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Admin @ si @ VBM2022 |
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3770 |
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Sergi Garcia Bordils; Andres Mafla; Ali Furkan Biten; Oren Nuriel; Aviad Aberdam; Shai Mazor; Ron Litman; Dimosthenis Karatzas |
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Out-of-Vocabulary Challenge Report |
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2022 |
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Proceedings European Conference on Computer Vision Workshops |
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13804 |
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359–375 |
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This paper presents final results of the Out-Of-Vocabulary 2022 (OOV) challenge. The OOV contest introduces an important aspect that is not commonly studied by Optical Character Recognition (OCR) models, namely, the recognition of unseen scene text instances at training time. The competition compiles a collection of public scene text datasets comprising of 326,385 images with 4,864,405 scene text instances, thus covering a wide range of data distributions. A new and independent validation and test set is formed with scene text instances that are out of vocabulary at training time. The competition was structured in two tasks, end-to-end and cropped scene text recognition respectively. A thorough analysis of results from baselines and different participants is presented. Interestingly, current state-of-the-art models show a significant performance gap under the newly studied setting. We conclude that the OOV dataset proposed in this challenge will be an essential area to be explored in order to develop scene text models that achieve more robust and generalized predictions. |
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Tel-Aviv; Israel; October 2022 |
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ECCVW |
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DAG; 600.155; 302.105; 611.002 |
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Admin @ si @ GMB2022 |
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3771 |
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Author |
Josep Llados; Gemma Sanchez |
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Title |
Symbol Recognition Using Graphs |
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Miscellaneous |
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2003 |
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Proceedings of 10th IEEE International Conference on Image Processing, vol II, 49–52 |
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Barcelona |
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DAG @ dag @ LlS2003 |
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383 |
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Author |
Philippe Dosch; Josep Llados |
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Title |
Vectorial Signatures for Symbol Discrimination |
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2003 |
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Proceedings of Fifth IAPR International Workshop on Graphics Recognition, 159–169 |
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DAG @ dag @ DoL2003 |
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373 |
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Gemma Sanchez; Josep Llados |
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Syntactic models to represent perceptually regular repetitive patterns in graphic documents |
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2003 |
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Proceedings of Fifth IAPR International Workshop on Graphics Recognition, 194–201 |
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DAG @ dag @ SaL2003 |
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417 |
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