Composed Image Retrieval for Training-Free Domain Conversion
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00382721" target="_blank" >RIV/68407700:21230/25:00382721 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/WACV61041.2025.00175" target="_blank" >https://doi.org/10.1109/WACV61041.2025.00175</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/WACV61041.2025.00175" target="_blank" >10.1109/WACV61041.2025.00175</a>
Alternative languages
Result language
angličtina
Original language name
Composed Image Retrieval for Training-Free Domain Conversion
Original language description
This work addresses composed image retrieval in the context of domain conversion, where the content of a query image is retrieved in the domain specified by the query text. We show that a strong vision-language model provides sufficient descriptive power without additional training. The query image is mapped to the text input space using textual inversion. Unlike common practice that invert in the continuous space of text tokens, we use the discrete word space via a nearest-neighbor search in a text vocabulary. With this inversion, the image is softly mapped across the vocabulary and is made more robust using retrieval-based augmentation. Database images are retrieved by a weighted ensemble of text queries combining mapped words with the domain text. Our method outperforms prior art by a large margin on standard and newly introduced benchmarks. Code: https://github.com/NikosEfth/freedom
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
ISBN
979-8-3315-1084-8
ISSN
2472-6737
e-ISSN
2642-9381
Number of pages
11
Pages from-to
1723-1733
Publisher name
IEEE
Place of publication
Piscataway
Event location
Tucson
Event date
Feb 28, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001481328900165