Published October 30, 2022
| Version Accepted Published version
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Exploiting CLIP-Based Multi-modal Approach for Artwork Classification and Retrieval
Authors/Creators
- 1. Università degli Studi di Firenze - MICC, Firenze, Italy
Description
In this work we investigate how recent CLIP model can be applied in several tasks in artwork domain. We perform exhaustive experiments on the NoisyArt dataset which is a collection of artwork images collected from public resources on the web. On such dataset CLIP achieve impressive results on (zero-shot) classification and promising results in both artwork-to-artwork and description-to-artwork domain.ù
Notes
This work has been partly supported by the project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101004545 - ReInHerit.
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Exploiting CLIP-Based Multi-modal Approach for Artwork Classification and Retrieval.pdf
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