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| Author | Arya Farkhondeh; Cristina Palmero; Simone Scardapane; Sergio Escalera | ||||
| Title | Towards Self-Supervised Gaze Estimation | Type | Miscellaneous | ||
| Year | 2022 | Publication | Arxiv | Abbreviated Journal | |
| Volume | Issue | Pages | |||
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| Abstract | Recent joint embedding-based self-supervised methods have surpassed standard supervised approaches on various image recognition tasks such as image classification. These self-supervised methods aim at maximizing agreement between features extracted from two differently transformed views of the same image, which results in learning an invariant representation with respect to appearance and geometric image transformations. However, the effectiveness of these approaches remains unclear in the context of gaze estimation, a structured regression task that requires equivariance under geometric transformations (e.g., rotations, horizontal flip). In this work, we propose SwAT, an equivariant version of the online clustering-based self-supervised approach SwAV, to learn more informative representations for gaze estimation. We demonstrate that SwAT, with ResNet-50 and supported with uncurated unlabeled face images, outperforms state-of-the-art gaze estimation methods and supervised baselines in various experiments. In particular, we achieve up to 57% and 25% improvements in cross-dataset and within-dataset evaluation tasks on existing benchmarks (ETH-XGaze, Gaze360, and MPIIFaceGaze). | ||||
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| Notes | HUPBA; no menciona | Approved | no | ||
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Admin @ si @ FPS2022 | Serial | 3822 | ||
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| Author | Alicia Fornes; Gemma Sanchez | ||||
| Title | Analysis and Recognition of Music Scores | Type | Book Chapter | ||
| Year | 2014 | Publication | Handbook of Document Image Processing and Recognition | Abbreviated Journal | |
| Volume | E | Issue | Pages | 749-774 | |
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| Abstract | The analysis and recognition of music scores has attracted the interest of researchers for decades. Optical Music Recognition (OMR) is a classical research field of Document Image Analysis and Recognition (DIAR), whose aim is to extract information from music scores. Music scores contain both graphical and textual information, and for this reason, techniques are closely related to graphics recognition and text recognition. Since music scores use a particular diagrammatic notation that follow the rules of music theory, many approaches make use of context information to guide the recognition and solve ambiguities. This chapter overviews the main Optical Music Recognition (OMR) approaches. Firstly, the different methods are grouped according to the OMR stages, namely, staff removal, music symbol recognition, and syntactical analysis. Secondly, specific approaches for old and handwritten music scores are reviewed. Finally, online approaches and commercial systems are also commented. | ||||
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| Publisher | Springer London | Place of Publication | Editor | D. Doermann; K. Tombre | |
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-0-85729-860-7 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG; ADAS; 600.076; 600.077 | Approved | no | ||
| Call Number |
Admin @ si @ FoS2014 | Serial | 2484 | ||
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| Author | Alicia Fornes; Bart Lamiroy | ||||
| Title | Graphics Recognition, Current Trends and Evolutions | Type | Book Whole | ||
| Year | 2018 | Publication | Graphics Recognition, Current Trends and Evolutions | Abbreviated Journal | |
| Volume | 11009 | Issue | Pages | ||
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| Abstract | This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Workshop on Graphics Recognition, GREC 2017, held in Kyoto, Japan, in November 2017.
The 10 revised full papers presented were carefully reviewed and selected from 14 initial submissions. They contain both classical and emerging topics of graphics rcognition, namely analysis and detection of diagrams, search and classification, optical music recognition, interpretation of engineering drawings and maps. |
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| Publisher | Springer International Publishing | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | ISBN | 978-3-030-02283-9 | Medium | ||
| Area | Expedition | Conference | |||
| Notes | DAG; 600.121 | Approved | no | ||
| Call Number |
Admin @ si @ FoL2018 | Serial | 3171 | ||
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| Author | Alicia Fornes; Xavier Otazu; Josep Llados | ||||
| Title | Show through cancellation and image enhancement by multiresolution contrast processing | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 200-204 | ||
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| Abstract | Historical documents suffer from different types of degradation and noise such as background variation, uneven illumination or dark spots. In case of double-sided documents, another common problem is that the back side of the document usually interferes with the front side because of the transparency of the document or ink bleeding. This effect is called the show through phenomenon. Many methods are developed to solve these problems, and in the case of show-through, by scanning and matching both the front and back sides of the document. In contrast, our approach is designed to use only one side of the scanned document. We hypothesize that show-trough are low contrast components, while foreground components are high contrast ones. A Multiresolution Contrast (MC) decomposition is presented in order to estimate the contrast of features at different spatial scales. We cancel the show-through phenomenon by thresholding these low contrast components. This decomposition is also able to enhance the image removing shadowed areas by weighting spatial scales. Results show that the enhanced images improve the readability of the documents, allowing scholars both to recover unreadable words and to solve ambiguities. | ||||
| Address | Washington; USA; August 2013 | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes | DAG; 602.006; 600.045; 600.061; 600.052;CIC | Approved | no | ||
| Call Number |
Admin @ si @ FOL2013 | Serial | 2241 | ||
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| Author | Josep Famadas; Meysam Madadi; Cristina Palmero; Sergio Escalera | ||||
| Title | Generative Video Face Reenactment by AUs and Gaze Regularization | Type | Conference Article | ||
| Year | 2020 | Publication | 15th IEEE International Conference on Automatic Face and Gesture Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 444-451 | ||
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| Abstract | In this work, we propose an encoder-decoder-like architecture to perform face reenactment in image sequences. Our goal is to transfer the training subject identity to a given test subject. We regularize face reenactment by facial action unit intensity and 3D gaze vector regression. This way, we enforce the network to transfer subtle facial expressions and eye dynamics, providing a more lifelike result. The proposed encoder-decoder receives as input the previous sequence frame stacked to the current frame image of facial landmarks. Thus, the generated frames benefit from appearance and geometry, while keeping temporal coherence for the generated sequence. At test stage, a new target subject with the facial performance of the source subject and the appearance of the training subject is reenacted. Principal component analysis is applied to project the test subject geometry to the closest training subject geometry before reenactment. Evaluation of our proposal shows faster convergence, and more accurate and realistic results in comparison to other architectures without action units and gaze regularization. | ||||
| Address | Virtual; November 2020 | ||||
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| Area | Expedition | Conference | FG | ||
| Notes | HUPBA | Approved | no | ||
| Call Number |
Admin @ si @ FMP2020 | Serial | 3517 | ||
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| Author | Alicia Fornes; Beata Megyesi; Joan Mas | ||||
| Title | Transcription of Encoded Manuscripts with Image Processing Techniques | Type | Conference Article | ||
| Year | 2017 | Publication | Digital Humanities Conference | Abbreviated Journal | |
| Volume | Issue | Pages | 441-443 | ||
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| Area | Expedition | Conference | DH | ||
| Notes | DAG; 600.097; 600.121 | Approved | no | ||
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Admin @ si @ FMM2017 | Serial | 3061 | ||
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| Author | David Fernandez; R.Manmatha; Josep Llados; Alicia Fornes | ||||
| Title | Sequential Word Spotting in Historical Handwritten Documents | Type | Conference Article | ||
| Year | 2014 | Publication | 11th IAPR International Workshop on Document Analysis and Systems | Abbreviated Journal | |
| Volume | Issue | Pages | 101 - 105 | ||
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| Abstract | In this work we present a handwritten word spotting approach that takes advantage of the a priori known order of appearance of the query words. Given an ordered sequence of query word instances, the proposed approach performs a
sequence alignment with the words in the target collection. Although the alignment is quite sparse, i.e. the number of words in the database is higher than the query set, the improvement in the overall performance is sensitively higher than isolated word spotting. As application dataset, we use a collection of handwritten marriage licenses taking advantage of the ordered index pages of family names. |
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| Address | Tours; Francia; April 2014 | ||||
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| ISSN | ISBN | 978-1-4799-3243-6 | Medium | ||
| Area | Expedition | Conference | DAS | ||
| Notes | DAG; 600.061; 600.056; 602.006; 600.077 | Approved | no | ||
| Call Number |
Admin @ si @ FML2014 | Serial | 2462 | ||
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| Author | David Fernandez; Simone Marinai; Josep Llados; Alicia Fornes | ||||
| Title | Contextual Word Spotting in Historical Manuscripts using Markov Logic Networks | Type | Conference Article | ||
| Year | 2013 | Publication | 2nd International Workshop on Historical Document Imaging and Processing | Abbreviated Journal | |
| Volume | Issue | Pages | 36-43 | ||
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| Abstract | Natural languages can often be modelled by suitable grammars whose knowledge can improve the word spotting results. The implicit contextual information is even more useful when dealing with information that is intrinsically described as one collection of records. In this paper, we present one approach to word spotting which uses the contextual information of records to improve the results. The method relies on Markov Logic Networks to probabilistically model the relational organization of handwritten records. The performance has been evaluated on the Barcelona Marriages Dataset that contains structured handwritten records that summarize marriage information. | ||||
| Address | washington; USA; August 2013 | ||||
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| ISSN | ISBN | 978-1-4503-2115-0 | Medium | ||
| Area | Expedition | Conference | HIP | ||
| Notes | DAG; 600.056; 600.045; 600.061; 602.006 | Approved | no | ||
| Call Number |
Admin @ si @ FML2013 | Serial | 2308 | ||
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| Author | Hao Fang; Ajian Liu; Jun Wan; Sergio Escalera; Chenxu Zhao; Xu Zhang; Stan Z Li; Zhen Lei | ||||
| Title | Surveillance Face Anti-spoofing | Type | Journal Article | ||
| Year | 2024 | Publication | IEEE Transactions on Information Forensics and Security | Abbreviated Journal | TIFS |
| Volume | 19 | Issue | Pages | 1535-1546 | |
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| Abstract | Face Anti-spoofing (FAS) is essential to secure face recognition systems from various physical attacks. However, recent research generally focuses on short-distance applications (i.e., phone unlocking) while lacking consideration of long-distance scenes (i.e., surveillance security checks). In order to promote relevant research and fill this gap in the community, we collect a large-scale Surveillance High-Fidelity Mask (SuHiFiMask) dataset captured under 40 surveillance scenes, which has 101 subjects from different age groups with 232 3D attacks (high-fidelity masks), 200 2D attacks (posters, portraits, and screens), and 2 adversarial attacks. In this scene, low image resolution and noise interference are new challenges faced in surveillance FAS. Together with the SuHiFiMask dataset, we propose a Contrastive Quality-Invariance Learning (CQIL) network to alleviate the performance degradation caused by image quality from three aspects: (1) An Image Quality Variable module (IQV) is introduced to recover image information associated with discrimination by combining the super-resolution network. (2) Using generated sample pairs to simulate quality variance distributions to help contrastive learning strategies obtain robust feature representation under quality variation. (3) A Separate Quality Network (SQN) is designed to learn discriminative features independent of image quality. Finally, a large number of experiments verify the quality of the SuHiFiMask dataset and the superiority of the proposed CQIL. | ||||
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| Notes | HUPBA | Approved | no | ||
| Call Number |
Admin @ si @ FLW2024 | Serial | 3869 | ||
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| Author | Hao Fang; Ajian Liu; Jun Wan; Sergio Escalera; Hugo Jair Escalante; Zhen Lei | ||||
| Title | Surveillance Face Presentation Attack Detection Challenge | Type | Conference Article | ||
| Year | 2023 | Publication | Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops | Abbreviated Journal | |
| Volume | Issue | Pages | 6360-6370 | ||
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| Abstract | Face Anti-spoofing (FAS) is essential to secure face recognition systems from various physical attacks. However, most of the studies lacked consideration of long-distance scenarios. Specifically, compared with FAS in traditional scenes such as phone unlocking, face payment, and self-service security inspection, FAS in long-distance such as station squares, parks, and self-service supermarkets are equally important, but it has not been sufficiently explored yet. In order to fill this gap in the FAS community, we collect a large-scale Surveillance High-Fidelity Mask (SuHiFiMask). SuHiFiMask contains 10,195 videos from 101 subjects of different age groups, which are collected by 7 mainstream surveillance cameras. Based on this dataset and protocol-3 for evaluating the robustness of the algorithm under quality changes, we organized a face presentation attack detection challenge in surveillance scenarios. It attracted 180 teams for the development phase with a total of 37 teams qualifying for the final round. The organization team re-verified and re-ran the submitted code and used the results as the final ranking. In this paper, we present an overview of the challenge, including an introduction to the dataset used, the definition of the protocol, the evaluation metrics, and the announcement of the competition results. Finally, we present the top-ranked algorithms and the research ideas provided by the competition for attack detection in long-range surveillance scenarios. | ||||
| Address | Vancouver; Canada; June 2023 | ||||
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| Area | Expedition | Conference | CVPRW | ||
| Notes | HuPBA | Approved | no | ||
| Call Number |
Admin @ si @ FLW2023 | Serial | 3917 | ||
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| Author | Onur Ferhat; Arcadi Llanza; Fernando Vilariño | ||||
| Title | Gaze interaction for multi-display systems using natural light eye-tracker | Type | Conference Article | ||
| Year | 2015 | Publication | 2nd International Workshop on Solutions for Automatic Gaze Data Analysis | Abbreviated Journal | |
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| Address | Bielefeld; Germany; September 2015 | ||||
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| Area | Expedition | Conference | SAGA | ||
| Notes | MV;SIAI | Approved | no | ||
| Call Number |
Admin @ si @ FLV2015b | Serial | 2676 | ||
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| Author | Onur Ferhat; Arcadi Llanza; Fernando Vilariño | ||||
| Title | A Feature-Based Gaze Estimation Algorithm for Natural Light Scenarios | Type | Conference Article | ||
| Year | 2015 | Publication | Pattern Recognition and Image Analysis, Proceedings of 7th Iberian Conference , ibPRIA 2015 | Abbreviated Journal | |
| Volume | 9117 | Issue | Pages | 569-576 | |
| Keywords | Eye tracking; Gaze estimation; Natural light; Webcam | ||||
| Abstract | We present an eye tracking system that works with regular webcams. We base our work on open source CVC Eye Tracker [7] and we propose a number of improvements and a novel gaze estimation method. The new method uses features extracted from iris segmentation and it does not fall into the traditional categorization of appearance–based/model–based methods. Our experiments show that our approach reduces the gaze estimation errors by 34 % in the horizontal direction and by 12 % in the vertical direction compared to the baseline system. | ||||
| Address | Santiago de Compostela; June 2015 | ||||
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| Publisher | Springer International Publishing | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0302-9743 | ISBN | 978-3-319-19389-2 | Medium | |
| Area | Expedition | Conference | IbPRIA | ||
| Notes | MV;SIAI | Approved | no | ||
| Call Number |
Admin @ si @ FLV2015a | Serial | 2646 | ||
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| Author | Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke | ||||
| Title | Writer Identification in Old Handwritten Music Scores | Type | Book Chapter | ||
| Year | 2012 | Publication | Pattern Recognition and Signal Processing in Archaeometry: Mathematical and Computational Solutions for Archaeology | Abbreviated Journal | |
| Volume | Issue | Pages | 27-63 | ||
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| Abstract | The aim of writer identification is determining the writer of a piece of handwriting from a set of writers. In this paper we present a system for writer identification in old handwritten music scores. Even though an important amount of compositions contains handwritten text in the music scores, the aim of our work is to use only music notation to determine the author. The steps of the system proposed are the following. First of all, the music sheet is preprocessed and normalized for obtaining a single binarized music line, without the staff lines. Afterwards, 100 features are extracted for every music line, which are subsequently used in a k-NN classifier that compares every feature vector with prototypes stored in a database. By applying feature selection and extraction methods on the original feature set, the performance is increased. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving a recognition rate of about 95%. | ||||
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| Publisher | IGI-Global | Place of Publication | Editor | Copnstantin Papaodysseus | |
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| Notes | DAG | Approved | no | ||
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Admin @ si @ FLS2012 | Serial | 1828 | ||
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| Author | Alicia Fornes; Josep Llados; Oriol Ramos Terrades; Marçal Rusiñol | ||||
| Title | La Visió per Computador com a Eina per a la Interpretació Automàtica de Fonts Documentals | Type | Journal | ||
| Year | 2016 | Publication | Lligall, Revista Catalana d'Arxivística | Abbreviated Journal | |
| Volume | 39 | Issue | Pages | 20-46 | |
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| Notes | DAG; 600.097 | Approved | no | ||
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Admin @ si @ FLR2016 | Serial | 2897 | ||
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| Author | Alicia Fornes; Josep Llados; Joana Maria Pujadas-Mora | ||||
| Title | Browsing of the Social Network of the Past: Information Extraction from Population Manuscript Images | Type | Book Chapter | ||
| Year | 2020 | Publication | Handwritten Historical Document Analysis, Recognition, and Retrieval – State of the Art and Future Trends | Abbreviated Journal | |
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| Publisher | World Scientific | Place of Publication | Editor | ||
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| ISSN | ISBN | 978-981-120-323-7 | Medium | ||
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| Notes | DAG; 600.140; 600.121 | Approved | no | ||
| Call Number |
Admin @ si @ FLP2020 | Serial | 3350 | ||
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