|
Records |
Links |
|
Author |
Cristina Sanchez Montes; F. Javier Sanchez; Cristina Rodriguez de Miguel; Henry Cordova; Jorge Bernal; Maria Lopez Ceron; Josep Llach; Gloria Fernandez Esparrach |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Histological Prediction Of Colonic Polyps By Computer Vision. Preliminary Results |
Type |
Conference Article |
|
Year |
2017 |
Publication |
25th United European Gastroenterology Week |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
|
|
|
Keywords |
polyps; histology; computer vision |
|
|
Abstract |
during colonoscopy, clinicians perform visual inspection of the polyps to predict histology. Kudo’s pit pattern classification is one of the most commonly used for optical diagnosis. These surface patterns present a contrast with respect to their neighboring regions and they can be considered as bright regions in the image that can attract the attention of computational methods. |
|
|
Address |
Barcelona; October 2017 |
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ESGE |
|
|
Notes |
MV; no menciona |
Approved |
no |
|
|
Call Number |
Admin @ si @ SSR2017 |
Serial |
2979 |
|
Permanent link to this record |
|
|
|
|
Author |
Maryam Asadi-Aghbolaghi; Albert Clapes; Marco Bellantonio; Hugo Jair Escalante; Victor Ponce; Xavier Baro; Isabelle Guyon; Shohreh Kasaei; Sergio Escalera |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
A survey on deep learning based approaches for action and gesture recognition in image sequences |
Type |
Conference Article |
|
Year |
2017 |
Publication |
12th IEEE International Conference on Automatic Face and Gesture Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
|
|
|
Keywords |
|
|
|
Abstract |
The interest in action and gesture recognition has grown considerably in the last years. In this paper, we present a survey on current deep learning methodologies for action and gesture recognition in image sequences. We introduce a taxonomy that summarizes important aspects of deep learning
for approaching both tasks. We review the details of the proposed architectures, fusion strategies, main datasets, and competitions.
We summarize and discuss the main works proposed so far with particular interest on how they treat the temporal dimension of data, discussing their main features and identify opportunities and challenges for future research. |
|
|
Address |
Washington; USA; May 2017 |
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
FG |
|
|
Notes |
HUPBA; no proj |
Approved |
no |
|
|
Call Number |
Admin @ si @ ACB2017b |
Serial |
2982 |
|
Permanent link to this record |
|
|
|
|
Author |
Ivet Rafegas; Maria Vanrell |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Color representation in CNNs: parallelisms with biological vision |
Type |
Conference Article |
|
Year |
2017 |
Publication |
ICCV Workshop on Mutual Benefits ofr Cognitive and Computer Vision |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
|
|
|
Keywords |
|
|
|
Abstract |
Convolutional Neural Networks (CNNs) trained for object recognition tasks present representational capabilities approaching to primate visual systems [1]. This provides a computational framework to explore how image features
are efficiently represented. Here, we dissect a trained CNN
[2] to study how color is represented. We use a classical methodology used in physiology that is measuring index of selectivity of individual neurons to specific features. We use ImageNet Dataset [20] images and synthetic versions
of them to quantify color tuning properties of artificial neurons to provide a classification of the network population.
We conclude three main levels of color representation showing some parallelisms with biological visual systems: (a) a decomposition in a circular hue space to represent single color regions with a wider hue sampling beyond the first
layer (V2), (b) the emergence of opponent low-dimensional spaces in early stages to represent color edges (V1); and (c) a strong entanglement between color and shape patterns representing object-parts (e.g. wheel of a car), objectshapes (e.g. faces) or object-surrounds configurations (e.g. blue sky surrounding an object) in deeper layers (V4 or IT). |
|
|
Address |
Venice; Italy; October 2017 |
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICCV-MBCC |
|
|
Notes |
CIC; 600.087; 600.051 |
Approved |
no |
|
|
Call Number |
Admin @ si @ RaV2017 |
Serial |
2984 |
|
Permanent link to this record |
|
|
|
|
Author |
Hana Jarraya; Oriol Ramos Terrades; Josep Llados |
![goto web page (via DOI) doi](img/doi.gif)
|
|
Title |
Learning structural loss parameters on graph embedding applied on symbolic graphs |
Type |
Conference Article |
|
Year |
2017 |
Publication |
12th IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
|
|
|
Keywords |
|
|
|
Abstract |
We propose an amelioration of proposed Graph Embedding (GEM) method in previous work that takes advantages of structural pattern representation and the structured distortion. it models an Attributed Graph (AG) as a Probabilistic Graphical Model (PGM). Then, it learns the parameters of this PGM presented by a vector, as new signature of AG in a lower dimensional vectorial space. We focus to adapt the structured learning algorithm via 1_slack formulation with a suitable risk function, called Graph Edit Distance (GED). It defines the dissimilarity of the ground truth and predicted graph labels. It determines by the error tolerant graph matching using bipartite graph matching algorithm. We apply Structured Support Vector Machines (SSVM) to process classification task. During our experiments, we got our results on the GREC dataset. |
|
|
Address |
Kyoto; Japan; November 2017 |
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
GREC |
|
|
Notes |
DAG; 600.097; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ JRL2017b |
Serial |
3073 |
|
Permanent link to this record |
|
|
|
|
Author |
Xavier Soria; Angel Sappa; Arash Akbarinia |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Multispectral Single-Sensor RGB-NIR Imaging: New Challenges and Opportunities |
Type |
Conference Article |
|
Year |
2017 |
Publication |
7th International Conference on Image Processing Theory, Tools & Applications |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
|
|
|
Keywords |
Color restoration; Neural networks; Singlesensor cameras; Multispectral images; RGB-NIR dataset |
|
|
Abstract |
Multispectral images captured with a single sensor camera have become an attractive alternative for numerous computer vision applications. However, in order to fully exploit their potentials, the color restoration problem (RGB representation) should be addressed. This problem is more evident in outdoor scenarios containing vegetation, living beings, or specular materials. The problem of color distortion emerges from the sensitivity of sensors due to the overlap of visible and near infrared spectral bands. This paper empirically evaluates the variability of the near infrared (NIR) information with respect to the changes of light throughout the day. A tiny neural network is proposed to restore the RGB color representation from the given RGBN (Red, Green, Blue, NIR) images. In order to evaluate the proposed algorithm, different experiments on a RGBN outdoor dataset are conducted, which include various challenging cases. The obtained result shows the challenge and the importance of addressing color restoration in single sensor multispectral images. |
|
|
Address |
Montreal; Canada; November 2017 |
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
IPTA |
|
|
Notes |
NEUROBIT; MSIAU; 600.122 |
Approved |
no |
|
|
Call Number |
Admin @ si @ SSA2017 |
Serial |
3074 |
|
Permanent link to this record |
|
|
|
|
Author |
Arash Akbarinia; Raquel Gil Rodriguez; C. Alejandro Parraga |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Colour Constancy: Biologically-inspired Contrast Variant Pooling Mechanism |
Type |
Conference Article |
|
Year |
2017 |
Publication |
28th British Machine Vision Conference |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
|
|
|
Keywords |
|
|
|
Abstract |
Pooling is a ubiquitous operation in image processing algorithms that allows for higher-level processes to collect relevant low-level features from a region of interest. Currently, max-pooling is one of the most commonly used operators in the computational literature. However, it can lack robustness to outliers due to the fact that it relies merely on the peak of a function. Pooling mechanisms are also present in the primate visual cortex where neurons of higher cortical areas pool signals from lower ones. The receptive fields of these neurons have been shown to vary according to the contrast by aggregating signals over a larger region in the presence of low contrast stimuli. We hypothesise that this contrast-variant-pooling mechanism can address some of the shortcomings of maxpooling. We modelled this contrast variation through a histogram clipping in which the percentage of pooled signal is inversely proportional to the local contrast of an image. We tested our hypothesis by applying it to the phenomenon of colour constancy where a number of popular algorithms utilise a max-pooling step (e.g. White-Patch, Grey-Edge and Double-Opponency). For each of these methods, we investigated the consequences of replacing their original max-pooling by the proposed contrast-variant-pooling. Our experiments on three colour constancy benchmark datasets suggest that previous results can significantly improve by adopting a contrast-variant-pooling mechanism. |
|
|
Address |
London; September 2017 |
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
BMVC |
|
|
Notes |
NEUROBIT; 600.068; 600.072 |
Approved |
no |
|
|
Call Number |
Admin @ si @ AGP2017 |
Serial |
2992 |
|
Permanent link to this record |
|
|
|
|
Author |
Arash Akbarinia; C. Alejandro Parraga; Marta Exposito; Bogdan Raducanu; Xavier Otazu |
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Can biological solutions help computers detect symmetry? |
Type |
Conference Article |
|
Year |
2017 |
Publication |
40th European Conference on Visual Perception |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
|
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Berlin; Germany; August 2017 |
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ECVP |
|
|
Notes |
NEUROBIT |
Approved |
no |
|
|
Call Number |
Admin @ si @ APE2017 |
Serial |
2995 |
|
Permanent link to this record |
|
|
|
|
Author |
J. Chazalon; P. Gomez-Kramer; Jean-Christophe Burie; M.Coustaty; S.Eskenazi; Muhammad Muzzamil Luqman; Nibal Nayef; Marçal Rusiñol; N. Sidere; Jean-Marc Ogier |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
SmartDoc 2017 Video Capture: Mobile Document Acquisition in Video Mode |
Type |
Conference Article |
|
Year |
2017 |
Publication |
1st International Workshop on Open Services and Tools for Document Analysis |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
|
|
|
Keywords |
|
|
|
Abstract |
As mobile document acquisition using smartphones is getting more and more common, along with the continuous improvement of mobile devices (both in terms of computing power and image quality), we can wonder to which extent mobile phones can replace desktop scanners. Modern applications can cope with perspective distortion and normalize the contrast of a document page captured with a smartphone, and in some cases like bottle labels or posters, smartphones even have the advantage of allowing the acquisition of non-flat or large documents. However, several cases remain hard to handle, such as reflective documents (identity cards, badges, glossy magazine cover, etc.) or large documents for which some regions require an important amount of detail. This paper introduces the SmartDoc 2017 benchmark (named “SmartDoc Video Capture”), which aims at
assessing whether capturing documents using the video mode of a smartphone could solve those issues. The task under evaluation is both a stitching and a reconstruction problem, as the user can move the device over different parts of the document to capture details or try to erase highlights. The material released consists of a dataset, an evaluation method and the associated tool, a sample method, and the tools required to extend the dataset. All the components are released publicly under very permissive licenses, and we particularly cared about maximizing the ease of
understanding, usage and improvement. |
|
|
Address |
Kyoto; Japan; November 2017 |
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICDAR-OST |
|
|
Notes |
DAG; 600.084; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ CGB2017 |
Serial |
2997 |
|
Permanent link to this record |
|
|
|
|
Author |
Lluis Gomez; Marçal Rusiñol; Dimosthenis Karatzas |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
LSDE: Levenshtein Space Deep Embedding for Query-by-string Word Spotting |
Type |
Conference Article |
|
Year |
2017 |
Publication |
14th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
|
|
|
Keywords |
|
|
|
Abstract |
n this paper we present the LSDE string representation and its application to handwritten word spotting. LSDE is a novel embedding approach for representing strings that learns a space in which distances between projected points are correlated with the Levenshtein edit distance between the original strings.
We show how such a representation produces a more semantically interpretable retrieval from the user’s perspective than other state of the art ones such as PHOC and DCToW. We also conduct a preliminary handwritten word spotting experiment on the George Washington dataset. |
|
|
Address |
Kyoto; Japan; November 2017 |
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICDAR |
|
|
Notes |
DAG; 600.084; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ GRK2017 |
Serial |
2999 |
|
Permanent link to this record |
|
|
|
|
Author |
E. Royer; J. Chazalon; Marçal Rusiñol; F. Bouchara |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Benchmarking Keypoint Filtering Approaches for Document Image Matching |
Type |
Conference Article |
|
Year |
2017 |
Publication |
14th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
|
|
|
Keywords |
|
|
|
Abstract |
Best Poster Award.
Reducing the amount of keypoints used to index an image is particularly interesting to control processing time and memory usage in real-time document image matching applications, like augmented documents or smartphone applications. This paper benchmarks two keypoint selection methods on a task consisting of reducing keypoint sets extracted from document images, while preserving detection and segmentation accuracy. We first study the different forms of keypoint filtering, and we introduce the use of the CORE selection method on
keypoints extracted from document images. Then, we extend a previously published benchmark by including evaluations of the new method, by adding the SURF-BRISK detection/description scheme, and by reporting processing speeds. Evaluations are conducted on the publicly available dataset of ICDAR2015 SmartDOC challenge 1. Finally, we prove that reducing the original keypoint set is always feasible and can be beneficial
not only to processing speed but also to accuracy. |
|
|
Address |
Kyoto; Japan; November 2017 |
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICDAR |
|
|
Notes |
DAG; 600.084; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ RCR2017 |
Serial |
3000 |
|
Permanent link to this record |
|
|
|
|
Author |
David Aldavert; Marçal Rusiñol; Ricardo Toledo |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Automatic Static/Variable Content Separation in Administrative Document Images |
Type |
Conference Article |
|
Year |
2017 |
Publication |
14th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
|
|
|
Keywords |
|
|
|
Abstract |
In this paper we present an automatic method for separating static and variable content from administrative document images. An alignment approach is able to unsupervisedly build probabilistic templates from a set of examples of the same document kind. Such templates define which is the likelihood of every pixel of being either static or variable content. In the extraction step, the same alignment technique is used to match
an incoming image with the template and to locate the positions where variable fields appear. We validate our approach on the public NIST Structured Tax Forms Dataset. |
|
|
Address |
Kyoto; Japan; November 2017 |
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICDAR |
|
|
Notes |
DAG; 600.084; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ ART2017 |
Serial |
3001 |
|
Permanent link to this record |
|
|
|
|
Author |
Arka Ujjal Dey; Suman Ghosh; Ernest Valveny |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
Don't only Feel Read: Using Scene text to understand advertisements |
Type |
Conference Article |
|
Year |
2018 |
Publication |
IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
|
|
|
Keywords |
|
|
|
Abstract |
We propose a framework for automated classification of Advertisement Images, using not just Visual features but also Textual cues extracted from embedded text. Our approach takes inspiration from the assumption that Ad images contain meaningful textual content, that can provide discriminative semantic interpretetion, and can thus aid in classifcation tasks. To this end, we develop a framework using off-the-shelf components, and demonstrate the effectiveness of Textual cues in semantic Classfication tasks. |
|
|
Address |
Salt Lake City; Utah; USA; June 2018 |
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
CVPRW |
|
|
Notes |
DAG; 600.121; 600.129 |
Approved |
no |
|
|
Call Number |
Admin @ si @ DGV2018 |
Serial |
3551 |
|
Permanent link to this record |
|
|
|
|
Author |
Leonardo Galteri; Dena Bazazian; Lorenzo Seidenari; Marco Bertini; Andrew Bagdanov; Anguelos Nicolaou; Dimosthenis Karatzas; Alberto del Bimbo |
![download PDF file pdf](img/file_PDF.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
Reading Text in the Wild from Compressed Images |
Type |
Conference Article |
|
Year |
2017 |
Publication |
1st International workshop on Egocentric Perception, Interaction and Computing |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
|
|
|
Keywords |
|
|
|
Abstract |
Reading text in the wild is gaining attention in the computer vision community. Images captured in the wild are almost always compressed to varying degrees, depending on application context, and this compression introduces artifacts
that distort image content into the captured images. In this paper we investigate the impact these compression artifacts have on text localization and recognition in the wild. We also propose a deep Convolutional Neural Network (CNN) that can eliminate text-specific compression artifacts and which leads to an improvement in text recognition. Experimental results on the ICDAR-Challenge4 dataset demonstrate that compression artifacts have a significant
impact on text localization and recognition and that our approach yields an improvement in both – especially at high compression rates. |
|
|
Address |
Venice; Italy; October 2017 |
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICCV - EPIC |
|
|
Notes |
DAG; 600.084; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ GBS2017 |
Serial |
3006 |
|
Permanent link to this record |
|
|
|
|
Author |
Andrei Polzounov; Artsiom Ablavatski; Sergio Escalera; Shijian Lu; Jianfei Cai |
![find record details (via OpenURL) openurl](img/xref.gif)
|
|
Title |
WordFences: Text Localization and Recognition |
Type |
Conference Article |
|
Year |
2017 |
Publication |
24th International Conference on Image Processing |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
|
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Beijing; China; September 2017 |
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICIP |
|
|
Notes |
HUPBA; no menciona |
Approved |
no |
|
|
Call Number |
Admin @ si @ PAE2017 |
Serial |
3007 |
|
Permanent link to this record |
|
|
|
|
Author |
Sergio Escalera; Xavier Baro; Hugo Jair Escalante; Isabelle Guyon |
![download PDF file pdf](img/file_PDF.gif)
|
|
Title |
ChaLearn Looking at People: A Review of Events and Resources |
Type |
Conference Article |
|
Year |
2017 |
Publication |
30th International Joint Conference on Neural Networks |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
|
|
|
Keywords |
|
|
|
Abstract |
This paper reviews the historic of ChaLearn Looking at People (LAP) events. We started in 2011 (with the release of the first Kinect device) to run challenges related to human action/activity and gesture recognition. Since then we have regularly organized events in a series of competitions covering all aspects of visual analysis of humans. So far we have organized more than 10 international challenges and events in this field. This paper reviews associated events, and introduces the ChaLearn LAP platform where public resources (including code, data and preprints of papers) related to the organized events are available. We also provide a discussion on perspectives of ChaLearn LAP activities. |
|
|
Address |
Anchorage; Alaska; USA; May 2017 |
|
|
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 |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
IJCNN |
|
|
Notes |
HuPBA; 602.143 |
Approved |
no |
|
|
Call Number |
Admin @ si @ EBE2017 |
Serial |
3012 |
|
Permanent link to this record |