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.| File | Dimensione | Formato | |
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3581783.3612664.pdf
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