KOPS - The Institutional Repository of the University of Konstanz

Color Composition Similarity and Its Application in Fine-grained Similarity

Color Composition Similarity and Its Application in Fine-grained Similarity

Cite This

Files in this item

Files Size Format View

There are no files associated with this item.

LAN HA, Mai, Vlad HOSU, Volker BLANZ, 2020. Color Composition Similarity and Its Application in Fine-grained Similarity. 2020 IEEE Winter Conference on Applications of Computer Vision (WACV). Snowmass, CO, Mar 1, 2020 - Mar 5, 2020. In: 2020 IEEE Winter Conference on Applications of Computer Vision (WACV). Piscataway, NJ:IEEE, pp. 2548-2557. eISSN 2642-9381. ISBN 978-1-72816-553-0. Available under: doi: 10.1109/WACV45572.2020.9093522

@inproceedings{LanHa2020Color-53099, title={Color Composition Similarity and Its Application in Fine-grained Similarity}, year={2020}, doi={10.1109/WACV45572.2020.9093522}, isbn={978-1-72816-553-0}, address={Piscataway, NJ}, publisher={IEEE}, booktitle={2020 IEEE Winter Conference on Applications of Computer Vision (WACV)}, pages={2548--2557}, author={Lan Ha, Mai and Hosu, Vlad and Blanz, Volker} }

<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/53099"> <dc:language>eng</dc:language> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dcterms:issued>2020</dcterms:issued> <dc:creator>Hosu, Vlad</dc:creator> <dcterms:title>Color Composition Similarity and Its Application in Fine-grained Similarity</dcterms:title> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/36"/> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dc:contributor>Blanz, Volker</dc:contributor> <dc:creator>Lan Ha, Mai</dc:creator> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/53099"/> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2021-03-08T10:04:07Z</dc:date> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/36"/> <dc:creator>Blanz, Volker</dc:creator> <dcterms:abstract xml:lang="eng">Assessing visual similarity in-the-wild, a core ability of the human visual system, is a challenging problem for computer vision methods because of its subjective nature and limited annotated datasets. We make a stride forward, showing that visual similarity can be better studied by isolating its components. We identify color composition similarity as an important aspect and study its interaction with category-level similarity. Color composition similarity considers the distribution of colors and their layout in images. We create predictive models accounting for the global similarity that is beyond pixel-based and patch-based, or histogram level information. Using an active learning approach, we build a large-scale color composition similarity dataset with subjective ratings via crowd-sourcing, the first of its kind. We train a Siamese network using the dataset to create a color similarity metric and descriptors which outperform existing color descriptors. We also provide a benchmark for global color descriptors for perceptual color similarity. Finally, we combine color similarity and category level features for fine-grained visual similarity. Our proposed model surpasses the state-of-the-art performance while using three orders of magnitude less training data. The results suggest that our proposal to study visual similarity by isolating its components, modeling and combining them is a promising paradigm for further development.</dcterms:abstract> <dc:contributor>Lan Ha, Mai</dc:contributor> <dc:contributor>Hosu, Vlad</dc:contributor> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2021-03-08T10:04:07Z</dcterms:available> </rdf:Description> </rdf:RDF>

This item appears in the following Collection(s)

Search KOPS


Browse

My Account