Detecting Unseen Visual Relations Using Analogies
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F19%3A00337253" target="_blank" >RIV/68407700:21730/19:00337253 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/ICCV.2019.00207" target="_blank" >https://doi.org/10.1109/ICCV.2019.00207</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICCV.2019.00207" target="_blank" >10.1109/ICCV.2019.00207</a>
Alternative languages
Result language
angličtina
Original language name
Detecting Unseen Visual Relations Using Analogies
Original language description
We seek to detect visual relations in images of the form of tripletst= (subject, predicate, object), such as “person riding dog”, where training examples of the individual entities are available but their combinations are unseen at training. This is an important set-up due to the combinatorial nature of visual relations: collecting sufficient training data for all possible triplets would be very hard. The contributions of this work are three-fold. First, we learn a representation of visual relations that combines (i) individual embeddings for subject, object and predicate together with(ii) a visual phrase embedding that represents the relation triplets. Second, we learn how to transfer visual phrase em-beddings from existing training triplets to unseen test triplets using analogies between relations that involve similar ob-jects. Third, we demonstrate the benefits of our approach on three challenging datasets: on HICO-DET, our model achieves significant improvement over a strong baseline for both frequent and unseen triplets, and we observe similar improvement for the retrieval of unseen triplets with out-of-vocabulary predicates on the COCO-a dataset as well as the challenging unusual triplets in the UnRel dataset.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF15_003%2F0000468" target="_blank" >EF15_003/0000468: Intelligent Machine Perception</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2019 IEEE International Conference on Computer Vision (ICCV 2019)
ISBN
978-1-7281-4804-5
ISSN
1550-5499
e-ISSN
2380-7504
Number of pages
10
Pages from-to
1981-1990
Publisher name
IEEE Computer Society Press
Place of publication
Los Alamitos
Event location
Seoul
Event date
Oct 27, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000531438102012