loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Rene Grzeszick and Gernot A. Fink

Affiliation: TU Dortmund University, Germany

Keyword(s): Zero-shot, Object Prediction, Scene Classification, Semantic Knowledge.

Abstract: This work focuses on the semantic relations between scenes and objects for visual object recognition. Semantic knowledge can be a powerful source of information especially in scenarios with few or no annotated training samples. These scenarios are referred to as zero-shot or few-shot recognition and often build on visual attributes. Here, instead of relying on various visual attributes, a more direct way is pursued: after recognizing the scene that is depicted in an image, semantic relations between scenes and objects are used for predicting the presence of objects in an unsupervised manner. Most importantly, relations between scenes and objects can easily be obtained from external sources such as large scale text corpora from the web and, therefore, do not require tremendous manual labeling efforts. It will be shown that in cluttered scenes, where visual recognition is difficult, scene knowledge is an important cue for predicting objects.

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 18.226.17.210

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:
Grzeszick, R. and Fink, G. (2017). Zero-shot Object Prediction using Semantic Scene Knowledge. In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 5: VISAPP; ISBN 978-989-758-226-4; ISSN 2184-4321, SciTePress, pages 120-129. DOI: 10.5220/0006240901200129

@conference{visapp17,
author={Rene Grzeszick. and Gernot A. Fink.},
title={Zero-shot Object Prediction using Semantic Scene Knowledge},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 5: VISAPP},
year={2017},
pages={120-129},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006240901200129},
isbn={978-989-758-226-4},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 5: VISAPP
TI - Zero-shot Object Prediction using Semantic Scene Knowledge
SN - 978-989-758-226-4
IS - 2184-4321
AU - Grzeszick, R.
AU - Fink, G.
PY - 2017
SP - 120
EP - 129
DO - 10.5220/0006240901200129
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