CLEAR: A Fully User-side Image Search System
Ryoma Sato

TL;DR
CLEAR is a fully user-side image search system that enables personalized, privacy-preserving similar-image searches on Flickr without relying on backend servers or stored indices.
Contribution
This paper presents the first practical implementation of a fully user-side image search system that operates without backend servers or stored images, demonstrating feasibility and customization.
Findings
Realizes a user-side similar image search engine for Flickr
Does not require backend servers or image storage
Enables easy deployment and privacy preservation
Abstract
We use many search engines on the Internet in our daily lives. However, they are not perfect. Their scoring function may not model our intent or they may accept only text queries even though we want to carry out a similar image search. In such cases, we need to make a compromise: We continue to use the unsatisfactory service or leave the service. Recently, a new solution, user-side search systems, has been proposed. In this framework, each user builds their own search system that meets their preference with a user-defined scoring function and user-defined interface. Although the concept is appealing, it is still not clear if this approach is feasible in practice. In this demonstration, we show the first fully user-side image search system, CLEAR, which realizes a similar-image search engine for Flickr. The challenge is that Flickr does not provide an official similar image search engine…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Image and Video Retrieval Techniques · Image Retrieval and Classification Techniques · Web Data Mining and Analysis
Methodstravel james
