Composed image retrieval extends traditional content-based image retrieval (CBIR) combining a query image with additional descriptive text to express user intent and specify supplementary requests related to the visual attributes of the query image. This approach holds significant potential for e-commerce applications, such as interactive multimodal searches and chatbots. In our demo, we present an interactive composed image retrieval system based on the SEARLE approach, which tackles this task in a zero-shot manner efficiently and effectively. The demo allows users to perform image retrieval iteratively refining the results using textual feedback.

Zero-Shot Image Retrieval with Human Feedback / Agnolucci, Lorenzo; Baldrati, Alberto; Bertini, Marco; Del Bimbo, Alberto. - ELETTRONICO. - (2023), pp. 9417-9419. ( ACM International Conference on Multimedia (ACM MM)) [10.1145/3581783.3612664].

Zero-Shot Image Retrieval with Human Feedback

Agnolucci, Lorenzo;Baldrati, Alberto;Bertini, Marco;Del Bimbo, Alberto
2023

Abstract

Composed image retrieval extends traditional content-based image retrieval (CBIR) combining a query image with additional descriptive text to express user intent and specify supplementary requests related to the visual attributes of the query image. This approach holds significant potential for e-commerce applications, such as interactive multimodal searches and chatbots. In our demo, we present an interactive composed image retrieval system based on the SEARLE approach, which tackles this task in a zero-shot manner efficiently and effectively. The demo allows users to perform image retrieval iteratively refining the results using textual feedback.
2023
Proc. of ACM International Conference on Multimedia (ACM MM)
ACM International Conference on Multimedia (ACM MM)
Agnolucci, Lorenzo; Baldrati, Alberto; Bertini, Marco; Del Bimbo, Alberto
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1452876
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