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Author David Geronimo; Antonio Lopez; Angel Sappa edit   pdf
url  openurl
  Title Computer Vision Approaches for Pedestrian Detection: Visible Spectrum Survey Type Conference Article
  Year 2007 Publication 3rd Iberian Conference on Pattern Recognition and Image Analysis, LNCS 4477 Abbreviated Journal  
  Volume 1 Issue Pages 547–554  
  Keywords Pedestrian detection  
  Abstract Pedestrian detection from images of the visible spectrum is a high relevant area of research given its potential impact in the design of pedestrian protection systems. There are many proposals in the literature but they lack a comparative viewpoint. According to this, in this paper we first propose a common framework where we fit the different approaches, and second we use this framework to provide a comparative point of view of the details of such different approaches, pointing out also the main challenges to be solved in the future. In summary, we expect
this survey to be useful for both novel and experienced researchers in the field. In the first case, as a clarifying snapshot of the state of the art; in the second, as a way to unveil trends and to take conclusions from the comparative study.		  
  Address Girona (Spain)  
  Corporate Author Thesis  
  Publisher Place of Publication Editor J. Marti et al.  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ GLS2007 Serial 804  
Permanent link to this record
 
 
Author Jaume Amores; Petia Radeva edit  url
doi  openurl
  Title Registration and Retrieval of Highly Elastic Bodies using Contextual Information Type Journal Article
  Year 2005 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 26 Issue 11 Pages 1720–1731  
  Keywords  
  Abstract IF: 1.138  
  Address  
  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  
  Notes ADAS;MILAB Approved no  
  Call Number ADAS @ adas @ AmR2005b Serial 592  
Permanent link to this record
 
 
Author Mikhail Mozerov; Ignasi Rius; Xavier Roca; Jordi Gonzalez edit   pdf
url  doi
openurl 
  Title Nonlinear synchronization for automatic learning of 3D pose variability in human motion sequences Type Journal Article
  Year 2010 Publication EURASIP Journal on Advances in Signal Processing Abbreviated Journal EURASIPJ  
  Volume Issue Pages  
  Keywords  
  Abstract Article ID 507247
A dense matching algorithm that solves the problem of synchronizing prerecorded human motion sequences, which show different speeds and accelerations, is proposed. The approach is based on minimization of MRF energy and solves the problem by using Dynamic Programming. Additionally, an optimal sequence is automatically selected from the input dataset to be a time-scale pattern for all other sequences. The paper utilizes an action specific model which automatically learns the variability of 3D human postures observed in a set of training sequences. The model is trained using the public CMU motion capture dataset for the walking action, and a mean walking performance is automatically learnt. Additionally, statistics about the observed variability of the postures and motion direction are also computed at each time step. The synchronized motion sequences are used to learn a model of human motion for action recognition and full-body tracking purposes.		  
  Address  
  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 1110-8657 ISBN Medium  
  Area Expedition Conference  
  Notes ISE Approved no  
  Call Number ISE @ ise @ MRR2010 Serial 1208  
Permanent link to this record
 
 
Author A. Gijsenij; Theo Gevers; Joost Van de Weijer edit  url
doi  isbn
openurl 
  Title Physics-based Edge Evaluation for Improved Color Constancy Type Conference Article
  Year 2009 Publication 22nd IEEE Conference on Computer Vision and Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 581 – 588  
  Keywords  
  Abstract Edge-based color constancy makes use of image derivatives to estimate the illuminant. However, different edge types exist in real-world images such as shadow, geometry, material and highlight edges. These different edge types may have a distinctive influence on the performance of the illuminant estimation.  
  Address Miami, USA  
  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 1063-6919 ISBN 978-1-4244-3992-8 Medium  
  Area Expedition Conference CVPR  
  Notes CAT;ISE Approved no  
  Call Number CAT @ cat @ GGW2009 Serial 1197  
Permanent link to this record
 
 
Author Marcos V Conde; Florin Vasluianu; Javier Vazquez; Radu Timofte edit   pdf
url  openurl
  Title Perceptual image enhancement for smartphone real-time applications Type Conference Article
  Year 2023 Publication Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Abbreviated Journal  
  Volume Issue Pages 1848-1858  
  Keywords  
  Abstract Recent advances in camera designs and imaging pipelines allow us to capture high-quality images using smartphones. However, due to the small size and lens limitations of the smartphone cameras, we commonly find artifacts or degradation in the processed images. The most common unpleasant effects are noise artifacts, diffraction artifacts, blur, and HDR overexposure. Deep learning methods for image restoration can successfully remove these artifacts. However, most approaches are not suitable for real-time applications on mobile devices due to their heavy computation and memory requirements. In this paper, we propose LPIENet, a lightweight network for perceptual image enhancement, with the focus on deploying it on smartphones. Our experiments show that, with much fewer parameters and operations, our model can deal with the mentioned artifacts and achieve competitive performance compared with state-of-the-art methods on standard benchmarks. Moreover, to prove the efficiency and reliability of our approach, we deployed the model directly on commercial smartphones and evaluated its performance. Our model can process 2K resolution images under 1 second in mid-level commercial smartphones.  
  Address Waikoloa; Hawai; USA; January 2023  
  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 WACV  
  Notes MACO; CIC Approved no  
  Call Number Admin @ si @ CVV2023 Serial 3900  
Permanent link to this record
 
 
Author Antonio Lopez; Cristina Cañero; Joan Serrat; J. Saludes; Felipe Lumbreras; T. Graf edit   pdf
url  openurl
  Title Detection of lane markings based on ridgeness and RANSAC Type Miscellaneous
  Year 2005 Publication Proceedings of the 8th International IEEE Conference on Intelligent Transportation Systems, 733–738 Abbreviated Journal  
  Volume Issue Pages  
  Keywords lane markings  
  Abstract  
  Address Vienna (Austria)  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes ADAS Approved no  
  Call Number ADAS @ adas @ LCS2005 Serial 588  
Permanent link to this record
 
 
Author Ruben Tito; Minesh Mathew; C.V. Jawahar; Ernest Valveny; Dimosthenis Karatzas edit   pdf
url  openurl
  Title ICDAR 2021 Competition on Document Visual Question Answering Type Conference Article
  Year 2021 Publication 16th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 635-649  
  Keywords  
  Abstract In this report we present results of the ICDAR 2021 edition of the Document Visual Question Challenges. This edition complements the previous tasks on Single Document VQA and Document Collection VQA with a newly introduced on Infographics VQA. Infographics VQA is based on a new dataset of more than 5, 000 infographics images and 30, 000 question-answer pairs. The winner methods have scored 0.6120 ANLS in Infographics VQA task, 0.7743 ANLSL in Document Collection VQA task and 0.8705 ANLS in Single Document VQA. We present a summary of the datasets used for each task, description of each of the submitted methods and the results and analysis of their performance. A summary of the progress made on Single Document VQA since the first edition of the DocVQA 2020 challenge is also presented.  
  Address VIRTUAL; Lausanne; Suissa; September 2021  
  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; 600.121 Approved no  
  Call Number Admin @ si @ TMJ2021 Serial 3624  
Permanent link to this record
 
 
Author Sergio Escalera; Ralf Herbrich edit  url
doi  isbn
openurl 
  Title The NeurIPS’18 Competition: From Machine Learning to Intelligent Conversations Type Book Whole
  Year 2020 Publication The Springer Series on Challenges in Machine Learning Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract This volume presents the results of the Neural Information Processing Systems Competition track at the 2018 NeurIPS conference. The competition follows the same format as the 2017 competition track for NIPS. Out of 21 submitted proposals, eight competition proposals were selected, spanning the area of Robotics, Health, Computer Vision, Natural Language Processing, Systems and Physics. Competitions have become an integral part of advancing state-of-the-art in artificial intelligence (AI). They exhibit one important difference to benchmarks: Competitions test a system end-to-end rather than evaluating only a single component; they assess the practicability of an algorithmic solution in addition to assessing feasibility.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor Sergio Escalera; Ralf Hebrick  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2520-1328 ISBN 978-3-030-29134-1 Medium  
  Area Expedition Conference  
  Notes HuPBA; no menciona Approved no  
  Call Number Admin @ si @ HeE2020 Serial 3328  
Permanent link to this record
 
 
Author Sergio Escalera; Stephane Ayache; Jun Wan; Meysam Madadi; Umut Guçlu; Xavier Baro edit  url
doi  openurl
  Title Inpainting and Denoising Challenges Type Book Whole
  Year 2019 Publication The Springer Series on Challenges in Machine Learning Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract The problem of dealing with missing or incomplete data in machine learning and computer vision arises in many applications. Recent strategies make use of generative models to impute missing or corrupted data. Advances in computer vision using deep generative models have found applications in image/video processing, such as denoising, restoration, super-resolution, or inpainting.
Inpainting and Denoising Challenges comprises recent efforts dealing with image and video inpainting tasks. This includes winning solutions to the ChaLearn Looking at People inpainting and denoising challenges: human pose recovery, video de-captioning and fingerprint restoration.
This volume starts with a wide review on image denoising, retracing and comparing various methods from the pioneer signal processing methods, to machine learning approaches with sparse and low-rank models, and recent deep learning architectures with autoencoders and variants. The following chapters present results from the Challenge, including three competition tasks at WCCI and ECML 2018. The top best approaches submitted by participants are described, showing interesting contributions and innovating methods. The last two chapters propose novel contributions and highlight new applications that benefit from image/video inpainting.		  
  Address  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes HUPBA; no menciona Approved no  
  Call Number Admin @ si @ EAW2019 Serial 3398  
Permanent link to this record
 
 
Author Alicia Fornes; Bart Lamiroy edit  url
isbn  openurl
  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  
  Keywords  
  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.		  
  Address  
  Corporate Author Thesis  
  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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