| Records |
| Author |
Rafael E. Rivadeneira, Angel D. Sappa and Boris X. Vintimilla |
| Title |
Multi-Image Super-Resolution for Thermal Images. |
Type |
Conference Article |
Year  |
2022 |
Publication |
Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2022 |
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4 |
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Pages |
635 - 642 |
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no |
| Call Number |
cidis @ cidis @ |
Serial |
181 |
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| Author |
Angel D. Sappa, Patricia L. Suárez, Henry O. Velesaca, Darío Carpio |
| Title |
Domain adaptation in image dehazing: exploring the usage of images from virtual scenarios. |
Type |
Conference Article |
| Year |
2022 |
Publication |
16th International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing (CGVCVIP 2022), julio 20-22 |
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85-92 |
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no |
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cidis @ cidis @ |
Serial |
182 |
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| Author |
Daniela Rato, Miguel Oliviera, Victor Santos, Manuel Gomes & Angel Sappa |
| Title |
A Sensor-to-Pattern Calibration Framework for Multi-Modal Industrial Collaborative Cells. |
Type |
Journal Article |
| Year |
2022 |
Publication |
Journal of Manufacturing Systems |
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Vol. 64 |
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Pages |
pp. 497-507 |
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yes |
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cidis @ cidis @ |
Serial |
184 |
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| Author |
Velesaca, Henry O.; Suárez, Patricia L.; Sappa, Angel D.; Carpio, Dario; Rivadeneira, Rafael E.; Sanchez, Angel |
| Title |
Review on Common Techniques for Urban Environment Video Analytics. |
Type |
Conference Article |
| Year |
2022 |
Publication |
WORKSHOP BRASILEIRO DE CIDADES INTELIGENTES (WBCI 2022) |
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Issue |
Porto Alegre: Sociedade Brasileira de Computação |
Pages |
107-118 |
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yes |
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cidis @ cidis @ |
Serial |
192 |
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| Author |
Jorge L. Charco, Angel D. Sappa, Boris X. Vintimilla |
| Title |
Human Pose Estimation through A Novel Multi-View Scheme |
Type |
Conference Article |
| Year |
2022 |
Publication |
Proceedings of the International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications VISIGRAPP 2022 |
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| Volume |
5 |
Issue |
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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. |
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Approved |
yes |
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cidis @ cidis @ |
Serial |
169 |
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| Author |
Xavier Soria , Gonzalo Pomboza-Junez & Angel Sappa. |
| Title |
LDC: Lightweight Dense CNN for Edge Detection. |
Type |
Journal Article |
| Year |
2022 |
Publication |
IEEE Access journal |
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| Volume |
Vol. 10 |
Issue |
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Pages |
pp. 68281-68290 |
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Approved |
yes |
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cidis @ cidis @ |
Serial |
183 |
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| Author |
Rivadeneira, Rafael E.; Sappa, Angel D. and Vintimilla Boris X. |
| Title |
Thermal Image Super-Resolution: A Novel Unsupervised Approach. |
Type |
Book Chapter |
| Year |
2022 |
Publication |
Communications in Computer and Information Science, 15th International Communications in Computer and Information Science Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications |
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BOOK |
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1474 |
Issue |
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Pages |
495-506 |
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Approved |
no |
| Call Number |
cidis @ cidis @ |
Serial |
179 |
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| Author |
Rafael E. Rivadeneira, Angel D. Sappa, Boris X. Vintimilla, Jin Kim, Dogun Kim et al. |
| Title |
Thermal Image Super-Resolution Challenge Results- PBVS 2022. |
Type |
Conference Article |
| Year |
2022 |
Publication |
Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. |
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CONFERENCE |
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2022-June |
Issue |
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Pages |
349-357 |
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| Abstract |
This paper presents results from the third Thermal Image
Super-Resolution (TISR) challenge organized in the Perception Beyond the Visible Spectrum (PBVS) 2022 workshop.
The challenge uses the same thermal image dataset as the
first two challenges, with 951 training images and 50 validation images at each resolution. A set of 20 images was
kept aside for testing. The evaluation tasks were to measure
the PSNR and SSIM between the SR image and the ground
truth (HR thermal noisy image downsampled by four), and
also to measure the PSNR and SSIM between the SR image
and the semi-registered HR image (acquired with another
camera). The results outperformed those from last year’s
challenge, improving both evaluation metrics. This year,
almost 100 teams participants registered for the challenge,
showing the community’s interest in this hot topic. |
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no |
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cidis @ cidis @ |
Serial |
175 |
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| Author |
Rangnekar,Aneesha; Mulhollan,Zachary; Vodacek,Anthony; Hoffman,Matthew; Sappa,Angel D.; Yu,Jun et al. |
| Title |
Semi-Supervised Hyperspectral Object Detection Challenge Results-PBVS 2022. |
Type |
Conference Article |
| Year |
2022 |
Publication |
Conference on Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. |
Abbreviated Journal |
CONFERENCE |
| Volume |
2022-June |
Issue |
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Pages |
389-397 |
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no |
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cidis @ cidis @ |
Serial |
176 |
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| Author |
Low S., Inkawhich N., Nina O., Sappa A. and Blasch E. |
| Title |
Multi-modal Aerial View Object Classification Challenge Results-PBVS 2022. |
Type |
Conference Article |
| Year |
2022 |
Publication |
Conference on Computer Vision and Pattern Recognition Workshops, (CVPRW 2022), junio 19-24. |
Abbreviated Journal |
CONFERENCE |
| Volume |
2022-June |
Issue |
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Pages |
417-425 |
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| Abstract |
This paper details the results and main findings of the
second iteration of the Multi-modal Aerial View Object
Classification (MAVOC) challenge. This year’s MAVOC
challenge is the second iteration. The primary goal of
both MAVOC challenges is to inspire research into methods for building recognition models that utilize both synthetic aperture radar (SAR) and electro-optical (EO) input
modalities. Teams are encouraged/challenged to develop
multi-modal approaches that incorporate complementary
information from both domains. While the 2021 challenge
showed a proof of concept that both modalities could be
used together, the 2022 challenge focuses on the detailed
multi-modal models. Using the same UNIfied COincident
Optical and Radar for recognitioN (UNICORN) dataset and
competition format that was used in 2021. Specifically, the
challenge focuses on two techniques, (1) SAR classification
and (2) SAR + EO classification. The bulk of this document is dedicated to discussing the top performing methods
and describing their performance on our blind test set. Notably, all of the top ten teams outperform our baseline. For
SAR classification, the top team showed a 129% improvement over our baseline and an 8% average improvement
from the 2021 winner. The top team for SAR + EO classification shows a 165% improvement with a 32% average
improvement over 2021. |
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cidis @ cidis @ |
Serial |
177 |
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