loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Donghwuy Ko ; Jongmin Yu ; Ahmad Muqeem Sheri and Moongu Jeon

Affiliation: Gwangju Institute of Science and Technology 123, Cheomdangwagi-ro, Buk-gu, Gwangju and South Korea

Keyword(s): Face Verification, Person Re-Identification, Unconstrained Condition, Metric Learning.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis

Abstract: Although various methods based on the hand-crafted features and deep learning methods have been developed for various applications in the past few years, distinguishing untrained identities in testing phase still remains a challenging task. To overcome these difficulties, we propose a novel representation learning approach to unconstrained face verification and open-world person re-identification tasks. Our approach aims to reinforce the discriminative power of learned features by assigning the weight to each training sample. We demonstrate the efficiency of the proposed method by testing on datasets which are publicly available. The experimental results for both face verification and person re-identification tasks show that its performance is comparable to state-of-the-art methods based on hand-crafted feature and general convolutional neural network.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.222.121.24

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Ko, D.; Yu, J.; Sheri, A. and Jeon, M. (2019). Unconstrained Face Verification and Open-World Person Re-identification via Densely-connected Convolution Neural Network. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP; ISBN 978-989-758-354-4; ISSN 2184-4321, SciTePress, pages 443-449. DOI: 10.5220/0007381104430449

@conference{visapp19,
author={Donghwuy Ko. and Jongmin Yu. and Ahmad Muqeem Sheri. and Moongu Jeon.},
title={Unconstrained Face Verification and Open-World Person Re-identification via Densely-connected Convolution Neural Network},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP},
year={2019},
pages={443-449},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007381104430449},
isbn={978-989-758-354-4},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP
TI - Unconstrained Face Verification and Open-World Person Re-identification via Densely-connected Convolution Neural Network
SN - 978-989-758-354-4
IS - 2184-4321
AU - Ko, D.
AU - Yu, J.
AU - Sheri, A.
AU - Jeon, M.
PY - 2019
SP - 443
EP - 449
DO - 10.5220/0007381104430449
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic