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Author | Eirikur Agustsson; Radu Timofte; Sergio Escalera; Xavier Baro; Isabelle Guyon; Rasmus Rothe | ||||
Title | Apparent and real age estimation in still images with deep residual regressors on APPA-REAL database | Type | Conference Article | ||
Year | 2017 | Publication | 12th IEEE International Conference on Automatic Face and Gesture Recognition | Abbreviated Journal | |
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Abstract | After decades of research, the real (biological) age estimation from a single face image reached maturity thanks to the availability of large public face databases and impressive accuracies achieved by recently proposed methods.
The estimation of “apparent age” is a related task concerning the age perceived by human observers. Significant advances have been also made in this new research direction with the recent Looking At People challenges. In this paper we make several contributions to age estimation research. (i) We introduce APPA-REAL, a large face image database with both real and apparent age annotations. (ii) We study the relationship between real and apparent age. (iii) We develop a residual age regression method to further improve the performance. (iv) We show that real age estimation can be successfully tackled as an apparent age estimation followed by an apparent to real age residual regression. (v) We graphically reveal the facial regions on which the CNN focuses in order to perform apparent and real age estimation tasks. |
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Address | Washington;USA; May 2017 | ||||
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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | FG | ||
Notes | HUPBA; no menciona | Approved | no | ||
Call Number | Admin @ si @ ATE2017 | Serial | 3013 | ||
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Author | Ekain Artola | ||||
Title | Human Attention Map Prediction Combining Visual Features | Type | Report | ||
Year | 2010 | Publication | CVC Technical Report | Abbreviated Journal | |
Volume | 160 | Issue | Pages | ||
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Corporate Author | Thesis | Bachelor's thesis | |||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
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Notes | Approved | no | |||
Call Number | Admin @ si @ Art2010 | Serial | 1352 | ||
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Author | Ekaterina Zaytseva; Jordi Vitria | ||||
Title | A search based approach to non maximum suppression in face detection | Type | Conference Article | ||
Year | 2012 | Publication | 19th IEEE International Conference on Image Processing | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | Poster
paper TA.P5.12 Face detectors typically produce a large number of false positives and this leads to the need to have a further non maximum suppression stage to eliminate multiple and spurious responses. This stage is based on considering spatial heuristics: true positive responses are selected by implicitly considering several restrictions on the spatial distribution of detector responses in natural images. In this paper we analyze the limitations of this approach and propose an efficient search method to overcome them. Results show how the application of this new non-maximum suppression approach to a simple face detector boosts its performance to state of the art results. |
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Address | Orlando; USA; September 2012 | ||||
Corporate Author | Thesis | ||||
Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 1522-4880 | ISBN | 978-1-4673-2534-9 | Medium | |
Area | Expedition | Conference | ICIP | ||
Notes | OR;MV | Approved | no | ||
Call Number | Admin @ si @ ZaV2012 | Serial | 2060 | ||
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Author | Ekaterina Zaytseva; Santiago Segui; Jordi Vitria | ||||
Title | Sketchable Histograms of Oriented Gradients for Object Detection | Type | Conference Article | ||
Year | 2012 | Publication | 17th Iberomerican Conference on Pattern Recognition | Abbreviated Journal | |
Volume | 7441 | Issue | Pages | 374-381 | |
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Abstract | In this paper we investigate a new representation approach for visual object recognition. The new representation, called sketchable-HoG, extends the classical histogram of oriented gradients (HoG) feature by adding two different aspects: the stability of the majority orientation and the continuity of gradient orientations. In this way, the sketchable-HoG locally characterizes the complexity of an object model and introduces global structure information while still keeping simplicity, compactness and robustness. We evaluated the proposed image descriptor on publicly Catltech 101 dataset. The obtained results outperforms classical HoG descriptor as well as other reported descriptors in the literature. | ||||
Address | Buenos Aires, Argentina | ||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-642-33274-6 | Medium | |
Area | Expedition | Conference | CIARP | ||
Notes | OR; MILAB;MV | Approved | no | ||
Call Number | Admin @ si @ ZSV2012 | Serial | 2048 | ||
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Author | Ekta Vats; Anders Hast; Alicia Fornes | ||||
Title | Training-Free and Segmentation-Free Word Spotting using Feature Matching and Query Expansion | Type | Conference Article | ||
Year | 2019 | Publication | 15th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 1294-1299 | ||
Keywords | Word spotting; Segmentation-free; Trainingfree; Query expansion; Feature matching | ||||
Abstract | Historical handwritten text recognition is an interesting yet challenging problem. In recent times, deep learning based methods have achieved significant performance in handwritten text recognition. However, handwriting recognition using deep learning needs training data, and often, text must be previously segmented into lines (or even words). These limitations constrain the application of HTR techniques in document collections, because training data or segmented words are not always available. Therefore, this paper proposes a training-free and segmentation-free word spotting approach that can be applied in unconstrained scenarios. The proposed word spotting framework is based on document query word expansion and relaxed feature matching algorithm, which can easily be parallelised. Since handwritten words posses distinct shape and characteristics, this work uses a combination of different keypoint detectors
and Fourier-based descriptors to obtain a sufficient degree of relaxed matching. The effectiveness of the proposed method is empirically evaluated on well-known benchmark datasets using standard evaluation measures. The use of informative features along with query expansion significantly contributed in efficient performance of the proposed method. |
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Address | Sydney; Australia; September 2019 | ||||
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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ICDAR | ||
Notes | DAG; 600.140; 600.121 | Approved | no | ||
Call Number | Admin @ si @ VHF2019 | Serial | 3356 | ||
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Author | Elena Valderrama; Joan Oliver; Josep Maria-Basart; Enric Marti; Petia Radeva; Ricardo Toledo; R.Vilanova;F.Ced; J.Muñoz; S.Vacchina | ||||
Title | Convergencia al EEES de la ingeniería informática. Título de Grado en tecnología (Informática) | Type | Miscellaneous | ||
Year | 2005 | Publication | I Jornades de Innovació Docent | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | Elena Valderrama | ||||
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Area | Expedition | Conference | |||
Notes | IAM;RV;MILAB;ADAS | Approved | no | ||
Call Number | IAM @ iam @ VOB2005 | Serial | 1652 | ||
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Author | Ellen J.L. Brunenberg; Oriol Pujol; Bart M. Ter Haar Romeny; Petia Radeva | ||||
Title | Automatic IVUS Segmentation of Atherosclerotic Plaque with Stop & Go Snake | Type | Miscellaneous | ||
Year | 2006 | Publication | 9th International Conference on Medical Image Computing and Computer–Assisted Intervention (MICCAI´06), 9–16 | Abbreviated Journal | |
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Address | Copenhagen (Denmark) | ||||
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Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
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Area | Expedition | Conference | |||
Notes | MILAB;HuPBA | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ BPT2006 | Serial | 767 | ||
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Author | Eloi Puertas; Miguel Angel Bautista; Daniel Sanchez; Sergio Escalera; Oriol Pujol | ||||
Title | Learning to Segment Humans by Stacking their Body Parts, | Type | Conference Article | ||
Year | 2014 | Publication | ECCV Workshop on ChaLearn Looking at People | Abbreviated Journal | |
Volume | 8925 | Issue | Pages | 685-697 | |
Keywords | Human body segmentation; Stacked Sequential Learning | ||||
Abstract | Human segmentation in still images is a complex task due to the wide range of body poses and drastic changes in environmental conditions. Usually, human body segmentation is treated in a two-stage fashion. First, a human body part detection step is performed, and then, human part detections are used as prior knowledge to be optimized by segmentation strategies. In this paper, we present a two-stage scheme based on Multi-Scale Stacked Sequential Learning (MSSL). We define an extended feature set by stacking a multi-scale decomposition of body
part likelihood maps. These likelihood maps are obtained in a first stage by means of a ECOC ensemble of soft body part detectors. In a second stage, contextual relations of part predictions are learnt by a binary classifier, obtaining an accurate body confidence map. The obtained confidence map is fed to a graph cut optimization procedure to obtain the final segmentation. Results show improved segmentation when MSSL is included in the human segmentation pipeline. |
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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 | ECCVW | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ PBS2014 | Serial | 2553 | ||
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Author | Eloi Puertas; Sergio Escalera; Oriol Pujol | ||||
Title | Classifying Objects at Different Sizes with Multi-Scale Stacked Sequential Learning | Type | Conference Article | ||
Year | 2010 | Publication | 13th International Conference of the Catalan Association for Artificial Intelligence | Abbreviated Journal | |
Volume | 220 | Issue | Pages | 193–200 | |
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Abstract | Sequential learning is that discipline of machine learning that deals with dependent data. In this paper, we use the Multi-scale Stacked Sequential Learning approach (MSSL) to solve the task of pixel-wise classification based on contextual information. The main contribution of this work is a shifting technique applied during the testing phase that makes possible, thanks to template images, to classify objects at different sizes. The results show that the proposed method robustly classifies such objects capturing their spatial relationships. | ||||
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Publisher | Place of Publication | Editor | R. Alquezar, A. Moreno, J. Aguilar | ||
Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | ISBN | 978-1-60750-642-3 | Medium | ||
Area | Expedition | Conference | CCIA | ||
Notes | HUPBA;MILAB | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ PEP2010 | Serial | 1448 | ||
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Author | Eloi Puertas; Sergio Escalera; Oriol Pujol | ||||
Title | Multi-Class Multi-Scale Stacked Sequential Learning | Type | Conference Article | ||
Year | 2011 | Publication | 10th International Conference on Multiple Classifier Systems | Abbreviated Journal | |
Volume | 6713 | Issue | Pages | 197-206 | |
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Address | Napoles, Italy | ||||
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Publisher | Springer | Place of Publication | Editor | Carlo Sansone; Josef Kittler; Fabio Roli | |
Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | MCS | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ PEP2011b | Serial | 1772 | ||
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Author | Eloi Puertas; Sergio Escalera; Oriol Pujol | ||||
Title | Generalized Multi-scale Stacked Sequential Learning for Multi-class Classification | Type | Journal Article | ||
Year | 2015 | Publication | Pattern Analysis and Applications | Abbreviated Journal | PAA |
Volume | 18 | Issue | 2 | Pages | 247-261 |
Keywords | Stacked sequential learning; Multi-scale; Error-correct output codes (ECOC); Contextual classification | ||||
Abstract | In many classification problems, neighbor data labels have inherent sequential relationships. Sequential learning algorithms take benefit of these relationships in order to improve generalization. In this paper, we revise the multi-scale sequential learning approach (MSSL) for applying it in the multi-class case (MMSSL). We introduce the error-correcting output codesframework in the MSSL classifiers and propose a formulation for calculating confidence maps from the margins of the base classifiers. In addition, we propose a MMSSL compression approach which reduces the number of features in the extended data set without a loss in performance. The proposed methods are tested on several databases, showing significant performance improvement compared to classical approaches. | ||||
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Publisher | Springer-Verlag | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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Series Volume | Series Issue | Edition | |||
ISSN | 1433-7541 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ PEP2013 | Serial | 2251 | ||
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Author | Elvina Motard; Bogdan Raducanu; Viviane Cadenat; Jordi Vitria | ||||
Title | Incremental On-Line Topological Map Learning for A Visual Homing Application | Type | Conference Article | ||
Year | 2007 | Publication | IEEE International Conference on Robotics and Automation | Abbreviated Journal | |
Volume | Issue | Pages | 2049–2054 | ||
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Abstract | |||||
Address | Roma (Italy) | ||||
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Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ICRA | ||
Notes | OR; MV | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ MRC2007 | Serial | 793 | ||
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Author | Emanuel Indermühle; Volkmar Frinken; Horst Bunke | ||||
Title | Mode Detection in Online Handwritten Documents using BLSTM Neural Networks | Type | Conference Article | ||
Year | 2012 | Publication | 13th International Conference on Frontiers in Handwriting Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 302-307 | ||
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Abstract | Mode detection in online handwritten documents refers to the process of distinguishing different types of contents, such as text, formulas, diagrams, or tables, one from another. In this paper a new approach to mode detection is proposed that uses bidirectional long-short term memory (BLSTM) neural networks. The BLSTM neural network is a novel type of recursive neural network that has been successfully applied in speech and handwriting recognition. In this paper we show that it has the potential to significantly outperform traditional methods for mode detection, which are usually based on stroke classification. As a further advantage over previous approaches, the proposed system is trainable and does not rely on user-defined heuristics. Moreover, it can be easily adapted to new or additional types of modes by just providing the system with new training data. | ||||
Address | Bari, italy | ||||
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Publisher | Place of Publication | Editor | |||
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ISSN | ISBN | 978-1-4673-2262-1 | Medium | ||
Area | Expedition | Conference | ICFHR | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ IFB2012 | Serial | 2056 | ||
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Author | Emanuel Sanchez Aimar; Petia Radeva; Mariella Dimiccoli | ||||
Title | Social Relation Recognition in Egocentric Photostreams | Type | Conference Article | ||
Year | 2019 | Publication | 26th International Conference on Image Processing | Abbreviated Journal | |
Volume | Issue | Pages | 3227-3231 | ||
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Abstract | This paper proposes an approach to automatically categorize the social interactions of a user wearing a photo-camera (2fpm), by relying solely on what the camera is seeing. The problem is challenging due to the overwhelming complexity of social life and the extreme intra-class variability of social interactions captured under unconstrained conditions. We adopt the formalization proposed in Bugental's social theory, that groups human relations into five social domains with related categories. Our method is a new deep learning architecture that exploits the hierarchical structure of the label space and relies on a set of social attributes estimated at frame level to provide a semantic representation of social interactions. Experimental results on the new EgoSocialRelation dataset demonstrate the effectiveness of our proposal. | ||||
Address | Taipei; Taiwan; September 2019 | ||||
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Publisher | Place of Publication | Editor | |||
Language | Summary Language | Original Title | |||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | ICIP | ||
Notes | MILAB; no menciona | Approved | no | ||
Call Number | Admin @ si @ SRD2019 | Serial | 3370 | ||
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Author | Emanuele Vivoli; Ali Furkan Biten; Andres Mafla; Dimosthenis Karatzas; Lluis Gomez | ||||
Title | MUST-VQA: MUltilingual Scene-text VQA | Type | Conference Article | ||
Year | 2022 | Publication | Proceedings European Conference on Computer Vision Workshops | Abbreviated Journal | |
Volume | 13804 | Issue | Pages | 345–358 | |
Keywords | Visual question answering; Scene text; Translation robustness; Multilingual models; Zero-shot transfer; Power of language models | ||||
Abstract | 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. | ||||
Address | Tel-Aviv; Israel; October 2022 | ||||
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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 | ECCVW | ||
Notes | DAG; 302.105; 600.155; 611.002 | Approved | no | ||
Call Number | Admin @ si @ VBM2022 | Serial | 3770 | ||
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