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Author |
Maria Oliver; Gloria Haro; Mariella Dimiccoli; Baptiste Mazin; Coloma Ballester |
![download PDF file pdf](img/file_PDF.gif)
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A computational model of amodal completion |
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Conference Article |
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2016 |
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SIAM Conference on Imaging Science |
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This paper presents a computational model to recover the most likely interpretation of the 3D scene structure from a planar image, where some objects may occlude others. The estimated scene interpretation is obtained by integrating some global and local cues and provides both the complete disoccluded objects that form the scene and their ordering according to depth. Our method first computes several distal scenes which are compatible with the proximal planar image. To compute these different hypothesized scenes, we propose a perceptually inspired object disocclusion method, which works by minimizing the Euler's elastica as well as by incorporating the relatability of partially occluded contours and the convexity of the disoccluded objects. Then, to estimate the preferred scene we rely on a Bayesian model and define probabilities taking into account the global complexity of the objects in the hypothesized scenes as well as the effort of bringing these objects in their relative position in the planar image, which is also measured by an Euler's elastica-based quantity. The model is illustrated with numerical experiments on, both, synthetic and real images showing the ability of our model to reconstruct the occluded objects and the preferred perceptual order among them. We also present results on images of the Berkeley dataset with provided figure-ground ground-truth labeling. |
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Albuquerque; New Mexico; USA; May 2016 |
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MILAB; 601.235 |
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Admin @ si @OHD2016a |
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2788 |
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G. de Oliveira; A. Cartas; Marc Bolaños; Mariella Dimiccoli; Xavier Giro; Petia Radeva |
![download PDF file pdf](img/file_PDF.gif)
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Title |
LEMoRe: A Lifelog Engine for Moments Retrieval at the NTCIR-Lifelog LSAT Task |
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2016 |
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12th NTCIR Conference on Evaluation of Information Access Technologies |
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Semantic image retrieval from large amounts of egocentric visual data requires to leverage powerful techniques for filling in the semantic gap. This paper introduces LEMoRe, a Lifelog Engine for Moments Retrieval, developed in the context of the Lifelog Semantic Access Task (LSAT) of the the NTCIR-12 challenge and discusses its performance variation on different trials. LEMoRe integrates classical image descriptors with high-level semantic concepts extracted by Convolutional Neural Networks (CNN), powered by a graphic user interface that uses natural language processing. Although this is just a first attempt towards interactive image retrieval from large egocentric datasets and there is a large room for improvement of the system components and the user interface, the structure of the system itself and the way the single components cooperate are very promising. |
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Tokyo; Japan; June 2016 |
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NTCIR |
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MILAB; |
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Admin @ si @OCB2016 |
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2789 |
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Author |
G. de Oliveira; Mariella Dimiccoli; Petia Radeva |
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Title |
Egocentric Image Retrieval With Deep Convolutional Neural Networks |
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2016 |
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19th International Conference of the Catalan Association for Artificial Intelligence |
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71-76 |
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Barcelona; Spain; October 2016 |
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CCIA |
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MILAB |
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Admin @ si @ODR2016 |
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2790 |
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Author |
Maedeh Aghaei; Mariella Dimiccoli; Petia Radeva |
![download PDF file pdf](img/file_PDF.gif)
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Title |
With whom do I interact with? Social interaction detection in egocentric photo-streams |
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Conference Article |
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2016 |
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23rd International Conference on Pattern Recognition |
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Given a user wearing a low frame rate wearable camera during a day, this work aims to automatically detect the moments when the user gets engaged into a social interaction solely by reviewing the automatically captured photos by the worn camera. The proposed method, inspired by the sociological concept of F-formation, exploits distance and orientation of the appearing individuals -with respect to the user- in the scene from a bird-view perspective. As a result, the interaction pattern over the sequence can be understood as a two-dimensional time series that corresponds to the temporal evolution of the distance and orientation features over time. A Long-Short Term Memory-based Recurrent Neural Network is then trained to classify each time series. Experimental evaluation over a dataset of 30.000 images has shown promising results on the proposed method for social interaction detection in egocentric photo-streams. |
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Cancun; Mexico; December 2016 |
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ICPR |
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MILAB |
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Admin @ si @ADR2016a |
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2791 |
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Author |
Mariella Dimiccoli; Petia Radeva |
![goto web page url](img/www.gif)
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Title |
Lifelogging in the era of outstanding digitization |
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2015 |
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International Conference on Digital Presentation and Preservation of Cultural and Scientific Heritage |
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In this paper, we give an overview on the emerging trend of the digitized self, focusing on visual lifelogging through wearable cameras. This is about continuously recording our life from a first-person view by wearing a camera that passively captures images. On one hand, visual lifelogging has opened the door to a large number of applications, including health. On the other, it has also boosted new challenges in the field of data analysis as well as new ethical concerns. While currently increasing efforts are being devoted to exploit lifelogging data for the improvement of personal well-being, we believe there are still many interesting applications to explore, ranging from tourism to the digitization of human behavior. |
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Verliko Tarmovo; Bulgaria; September 2015 |
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DiPP |
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MILAB |
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Admin @ si @DiR2016 |
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2792 |
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Author |
Aniol Lidon; Xavier Giro; Marc Bolaños; Petia Radeva; Markus Seidl; Matthias Zeppelzauer |
![goto web page url](img/www.gif)
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UPC-UB-STP @ MediaEval 2015 diversity task: iterative reranking of relevant images |
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2015 |
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2015 MediaEval Retrieving Diverse Images Task |
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This paper presents the results of the UPC-UB-STP team in the 2015 MediaEval Retrieving Diverse Images Task. The goal of the challenge is to provide a ranked list of Flickr photos for a predefined set of queries. Our approach firstly generates a ranking of images based on a query-independent estimation of its relevance. Only top results are kept and iteratively re-ranked based on their intra-similarity to introduce diversity. |
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Wurzen; Germany; September 2015 |
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MediaEval |
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MILAB |
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Admin @ si @LGB2016 |
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2793 |
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Author |
Jose Manuel Alvarez; Theo Gevers; Antonio Lopez |
![goto web page url](img/www.gif)
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Title |
Evaluating Color Representation for Online Road Detection |
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Conference Article |
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2013 |
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ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars |
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594-595 |
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Detecting traversable road areas ahead a moving vehicle is a key process for modern autonomous driving systems. Most existing algorithms use color to classify pixels as road or background. These algorithms reduce the effect of lighting variations and weather conditions by exploiting the discriminant/invariant properties of different color representations. However, up to date, no comparison between these representations have been conducted. Therefore, in this paper, we perform an evaluation of existing color representations for road detection. More specifically, we focus on color planes derived from RGB data and their most com-
mon combinations. The evaluation is done on a set of 7000 road images acquired
using an on-board camera in different real-driving situations. |
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CVVT:E2M |
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ADAS;ISE |
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Admin @ si @ AGL2013 |
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2794 |
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Author |
Y. Patel; Lluis Gomez; Marçal Rusiñol; Dimosthenis Karatzas |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Dynamic Lexicon Generation for Natural Scene Images |
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Conference Article |
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2016 |
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14th European Conference on Computer Vision Workshops |
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395-410 |
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scene text; photo OCR; scene understanding; lexicon generation; topic modeling; CNN |
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Many scene text understanding methods approach the endtoend recognition problem from a word-spotting perspective and take huge benet from using small per-image lexicons. Such customized lexicons are normally assumed as given and their source is rarely discussed.
In this paper we propose a method that generates contextualized lexicons
for scene images using only visual information. For this, we exploit
the correlation between visual and textual information in a dataset consisting
of images and textual content associated with them. Using the topic modeling framework to discover a set of latent topics in such a dataset allows us to re-rank a xed dictionary in a way that prioritizes the words that are more likely to appear in a given image. Moreover, we train a CNN that is able to reproduce those word rankings but using only the image raw pixels as input. We demonstrate that the quality of the automatically obtained custom lexicons is superior to a generic frequency-based baseline. |
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Amsterdam; The Netherlands; October 2016 |
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ECCVW |
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DAG; 600.084 |
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Admin @ si @ PGR2016 |
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2825 |
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Author |
Dan Norton; Fernando Vilariño; Onur Ferhat |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Memory Field – Creative Engagement in Digital Collections |
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2015 |
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Internet Librarian International Conference |
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“Memory Fields” is a trans-disciplinary project aiming at the (re)valorisation of digital collections.Its main deliverable is an interface for a dual screen installation, used to access and mix the public library digital collections. The collections being used in this case are a collection of digitised posters from the Spanish Civil War, belonging to the Arxiu General de Catalunya, and a collection of field recordings made by Dan Norton. The system generates visualisations, and the images and sounds are mixed together using narrative primitives of video dj. Users contribute to the digital collections by adding personal memories and observations. The comments and recollections appear as flowers growing in a “memory field” and memories remain public in a Twitter feed (@Memoryfields). |
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London; UK; October 2015 |
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ILI |
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MV;SIAI |
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Admin @ si @NVF2015 |
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2796 |
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Fernando Vilariño; Dimosthenis Karatzas |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
The Library Living Lab |
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2015 |
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Open Living Lab Days |
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Istanbul; Turkey; August 2015 |
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OLLD |
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MV; DAG;SIAI |
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Admin @ si @ViK2015 |
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2797 |
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Fernando Vilariño; Dimosthenis Karatzas; Marcos Catalan; Alberto Valcarcel |
![find record details (via OpenURL) openurl](img/xref.gif)
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An horizon for the Public Library as a place for innovation and creativity. The Library Living Lab in Volpelleres |
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2015 |
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The White Book on Public Library Network from Diputació de Barcelona |
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MV; DAG;SIAI |
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Admin @ si @VKC2015 |
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Fernando Vilariño |
![find record details (via OpenURL) openurl](img/xref.gif)
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Computer Vision and Performing Arts |
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2015 |
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Korean Scholars of Marketing Science |
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Seoul; Korea; October 2015 |
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KAMS |
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MV;SIAI |
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Admin @ si @Vil2015 |
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2799 |
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Fernando Vilariño; Dan Norton; Onur Ferhat |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Memory Fields: DJs in the Library |
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Conference Article |
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2015 |
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21 st Symposium of Electronic Arts |
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Vancouver; Canada; August 2015 |
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;SIAI |
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Admin @ si @VNF2015 |
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2800 |
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Fernando Vilariño; Dan Norton; Onur Ferhat |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
The Eye Doesn't Click – Eyetracking and Digital Content Interaction |
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2016 |
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4S/EASST Conference |
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Barcelona; Spain; September 2016 |
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MV; 600.097;SIAI |
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Admin @ si @VNF2016 |
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2801 |
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Author |
Fernando Vilariño |
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Title |
Giving Value to digital collections in the Public Library |
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Conference Article |
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2016 |
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Librarian 2020 |
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Brussels; Belgium; October 2016 |
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LIB |
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MV; 600.097;SIAI |
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no |
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Admin @ si @Vil2016a |
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2802 |
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