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Author David Geronimo; Antonio Lopez; Angel Sappa
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
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
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 Arjan Gijsenij; Theo Gevers; Joost Van de Weijer
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
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
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
Series Volume Series Issue Edition
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
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
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
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
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 HUPBA; no menciona Approved no
Call Number Admin @ si @ EAW2019 Serial 3398
Permanent link to this record
 
 
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
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
Permanent link to this record
 
 
Author Rafael E. Rivadeneira; Angel Sappa; Boris X. Vintimilla
Title Multi-Image Super-Resolution for Thermal Images Type Conference Article
Year 2022 Publication 17th International Conference on Computer Vision Theory and Applications (VISAPP 2022) Abbreviated Journal
Volume 4 Issue Pages 635-642
Keywords Thermal Images; Multi-view; Multi-frame; Super-Resolution; Deep Learning; Attention Block
Abstract This paper proposes a novel CNN architecture for the multi-thermal image super-resolution problem. In the proposed scheme, the multi-images are synthetically generated by downsampling and slightly shifting the given image; noise is also added to each of these synthesized images. The proposed architecture uses two
attention blocks paths to extract high-frequency details taking advantage of the large information extracted from multiple images of the same scene. Experimental results are provided, showing the proposed scheme has overcome the state-of-the-art approaches.
Address Online; Feb 6-8, 2022
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 VISAPP
Notes MSIAU; 601.349 Approved no
Call Number Admin @ si @ RSV2022a Serial 3690
Permanent link to this record
 
 
Author Giovanni Maria Farinella; Petia Radeva; Jose Braz; Kadi Bouatouch
Title Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (Volume 4) Type Book Whole
Year 2021 Publication Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. VISIGRAPP 2021 Abbreviated Journal
Volume 4 Issue Pages
Keywords
Abstract This book contains the proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) which was organized and sponsored by the Institute for Systems and Technologies of Information, Control and Communication (INSTICC), endorsed by the International Association for Pattern Recognition (IAPR), and in cooperation with the ACM Special Interest Group on Graphics and Interactive Techniques (SIGGRAPH), the European Association for Computer Graphics (EUROGRAPHICS), the EUROGRAPHICS Portuguese Chapter, the VRVis Center for Virtual Reality and Visualization Forschungs-GmbH, the French Association for Computer Graphics (AFIG), and the Society for Imaging Science and Technology (IS&T). The proceedings here published demonstrate new and innovative solutions and highlight technical problems in each field that are challenging and worthy of being disseminated to the interested research audiences. VISIGRAPP 2021 was organized to promote a discussion forum about the conference’s research topics between researchers, developers, manufacturers and end-users, and to establish guidelines in the development of more advanced solutions. This year VISIGRAPP was, exceptionally, held as a web-based event, due to the COVID-19 pandemic, from 8 – 10 February. We received a high number of paper submissions for this edition of VISIGRAPP, 371 in total, with contributions from 52 countries. This attests to the success and global dimension of VISIGRAPP. To evaluate each submission, we used a hierarchical process of double-blind evaluation where each paper was reviewed by two to six experts from the International Program Committee (IPC). The IPC selected for oral presentation and for publication as full papers 12 papers from GRAPP, 8 from HUCAPP, 11 papers from IVAPP, and 56 papers from VISAPP, which led to a result for the full-paper acceptance ratio of 24% and a high-quality program. Apart from the above full papers, the conference program also features 118 short papers and 67 poster presentations. We hope that these conference proceedings, which are submitted for indexation by Thomson Reuters Conference Proceedings Citation Index, SCOPUS, DBLP, Semantic Scholar, Google Scholar, EI and Microsoft Academic, will help the Computer Vision, Imaging, Visualization, Computer Graphics and Human-Computer Interaction communities to find interesting research work. Moreover, we are proud to inform that the program also includes three plenary keynote lectures, given by internationally distinguished researchers, namely Federico Tombari (Google and Technical University of Munich, Germany), Dieter Schmalstieg (Graz University of Technology, Austria) and Nathalie Henry Riche (Microsoft Research, United States), thus contributing to increase the overall quality of the conference and to provide a deeper understanding of the conference’s interest fields. Furthermore, a short list of the presented papers will be selected to be extended into a forthcoming book of VISIGRAPP Selected Papers to be published by Springer during 2021 in the CCIS series. Moreover, a short list of presented papers will be selected for publication of extended and revised versions in a special issue of the Springer Nature Computer Science journal. All papers presented at this conference will be available at the SCITEPRESS Digital Library. Three awards are delivered at the closing session, to recognize the best conference paper, the best student paper and the best poster for each of the four conferences. There is also an award for best industrial paper to be delivered at the closing session for VISAPP. We would like to express our thanks, first of all, to the authors of the technical papers, whose work and dedication made it possible to put together a program that we believe to be very exciting and of high technical quality. Next, we would like to thank the Area Chairs, all the members of the program committee and auxiliary reviewers, who helped us with their expertise and time. We would also like to thank the invited speakers for their invaluable contribution and for sharing their vision in their talks. Finally, we gratefully acknowledge the professional support of the INSTICC team for all organizational processes, especially given the need to introduce online streaming, forum management, direct messaging facilitation and other web-based activities in order to make it possible for VISIGRAPP 2021 authors to present their work and share ideas with colleagues in spite of the logistic difficulties caused by the current pandemic situation. We wish you all an exciting conference. We hope to meet you again for the next edition of VISIGRAPP, details of which are available at http://www. visigrapp.org
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 VISIGRAPP
Notes MILAB Approved no
Call Number Admin @ si @ FRB2021a Serial 3627
Permanent link to this record
 
 
Author Giovanni Maria Farinella; Petia Radeva; Jose Braz; Kadi Bouatouch
Title Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications – (Volume 5) Type Book Whole
Year 2021 Publication Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications – VISIGRAPP 2021 Abbreviated Journal
Volume 5 Issue Pages
Keywords
Abstract This book contains the proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) which was organized and sponsored by the Institute for Systems and Technologies of Information, Control and Communication (INSTICC), endorsed by the International Association for Pattern Recognition (IAPR), and in cooperation with the ACM Special Interest Group on Graphics and Interactive Techniques (SIGGRAPH), the European Association for Computer Graphics (EUROGRAPHICS), the EUROGRAPHICS Portuguese Chapter, the VRVis Center for Virtual Reality and Visualization Forschungs-GmbH, the French Association for Computer Graphics (AFIG), and the Society for Imaging Science and Technology (IS&T). The proceedings here published demonstrate new and innovative solutions and highlight technical problems in each field that are challenging and worthy of being disseminated to the interested research audiences. VISIGRAPP 2021 was organized to promote a discussion forum about the conference’s research topics between researchers, developers, manufacturers and end-users, and to establish guidelines in the development of more advanced solutions. This year VISIGRAPP was, exceptionally, held as a web-based event, due to the COVID-19 pandemic, from 8 – 10 February. We received a high number of paper submissions for this edition of VISIGRAPP, 371 in total, with contributions from 52 countries. This attests to the success and global dimension of VISIGRAPP. To evaluate each submission, we used a hierarchical process of double-blind evaluation where each paper was reviewed by two to six experts from the International Program Committee (IPC). The IPC selected for oral presentation and for publication as full papers 12 papers from GRAPP, 8 from HUCAPP, 11 papers from IVAPP, and 56 papers from VISAPP, which led to a result for the full-paper acceptance ratio of 24% and a high-quality program. Apart from the above full papers, the conference program also features 118 short papers and 67 poster presentations. We hope that these conference proceedings, which are submitted for indexation by Thomson Reuters Conference Proceedings Citation Index, SCOPUS, DBLP, Semantic Scholar, Google Scholar, EI and Microsoft Academic, will help the Computer Vision, Imaging, Visualization, Computer Graphics and Human-Computer Interaction communities to find interesting research work. Moreover, we are proud to inform that the program also includes three plenary keynote lectures, given by internationally distinguished researchers, namely Federico Tombari (Google and Technical University of Munich, Germany), Dieter Schmalstieg (Graz University of Technology, Austria) and Nathalie Henry Riche (Microsoft Research, United States), thus contributing to increase the overall quality of the conference and to provide a deeper understanding of the conference’s interest fields. Furthermore, a short list of the presented papers will be selected to be extended into a forthcoming book of VISIGRAPP Selected Papers to be published by Springer during 2021 in the CCIS series. Moreover, a short list of presented papers will be selected for publication of extended and revised versions in a special issue of the Springer Nature Computer Science journal. All papers presented at this conference will be available at the SCITEPRESS Digital Library. Three awards are delivered at the closing session, to recognize the best conference paper, the best student paper and the best poster for each of the four conferences. There is also an award for best industrial paper to be delivered at the closing session for VISAPP. We would like to express our thanks, first of all, to the authors of the technical papers, whose work and dedication made it possible to put together a program that we believe to be very exciting and of high technical quality. Next, we would like to thank the Area Chairs, all the members of the program committee and auxiliary reviewers, who helped us with their expertise and time. We would also like to thank the invited speakers for their invaluable contribution and for sharing their vision in their talks. Finally, we gratefully acknowledge the professional support of the INSTICC team for all organizational processes, especially given the need to introduce online streaming, forum management, direct messaging facilitation and other web-based activities in order to make it possible for VISIGRAPP 2021 authors to present their work and share ideas with colleagues in spite of the logistic difficulties caused by the current pandemic situation. We wish you all an exciting conference. We hope to meet you again for the next edition of VISIGRAPP, details of which are available at http://www. visigrapp.org.
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 VISIGRAPP
Notes MILAB Approved no
Call Number Admin @ si @ FRB2021b Serial 3628
Permanent link to this record
 
 
Author Bhalaji Nagarajan; Ricardo Marques; Marcos Mejia; Petia Radeva
Title Class-conditional Importance Weighting for Deep Learning with Noisy Labels Type Conference Article
Year 2022 Publication 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications Abbreviated Journal
Volume 5 Issue Pages 679-686
Keywords Noisy Labeling; Loss Correction; Class-conditional Importance Weighting; Learning with Noisy Labels
Abstract Large-scale accurate labels are very important to the Deep Neural Networks to train them and assure high performance. However, it is very expensive to create a clean dataset since usually it relies on human interaction. To this purpose, the labelling process is made cheap with a trade-off of having noisy labels. Learning with Noisy Labels is an active area of research being at the same time very challenging. The recent advances in Self-supervised learning and robust loss functions have helped in advancing noisy label research. In this paper, we propose a loss correction method that relies on dynamic weights computed based on the model training. We extend the existing Contrast to Divide algorithm coupled with DivideMix using a new class-conditional weighted scheme. We validate the method using the standard noise experiments and achieved encouraging results.
Address Virtual; February 2022
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 VISAPP
Notes MILAB; no menciona Approved no
Call Number Admin @ si @ NMM2022 Serial 3798
Permanent link to this record
 
 
Author Jorge Charco; Angel Sappa; Boris X. Vintimilla
Title Human Pose Estimation through a Novel Multi-view Scheme Type Conference Article
Year 2022 Publication 17th International Conference on Computer Vision Theory and Applications (VISAPP 2022) Abbreviated Journal
Volume 5 Issue Pages 855-862
Keywords Multi-view Scheme; Human Pose Estimation; Relative Camera Pose; Monocular Approach
Abstract This paper presents a multi-view scheme to tackle the challenging problem of the self-occlusion in human pose estimation problem. The proposed approach first obtains the human body joints of a set of images, which are captured from different views at the same time. Then, it enhances the obtained joints by using a
multi-view scheme. Basically, the joints from a given view are used to enhance poorly estimated joints from another view, especially intended to tackle the self occlusions cases. A network architecture initially proposed for the monocular case is adapted to be used in the proposed multi-view scheme. Experimental results and
comparisons with the state-of-the-art approaches on Human3.6m dataset are presented showing improvements in the accuracy of body joints estimations.
Address On line; Feb 6, 2022 – Feb 8, 2022
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 2184-4321 ISBN 978-989-758-555-5 Medium
Area Expedition Conference VISAPP
Notes MSIAU; 600.160 Approved no
Call Number Admin @ si @ CSV2022 Serial 3689
Permanent link to this record