SOTAVerified

Content-Based Image Retrieval

Content-Based Image Retrieval is a well studied problem in computer vision, with retrieval problems generally divided into two groups: category-level retrieval and instance-level retrieval. Given a query image of the Sydney Harbour bridge, for instance, category-level retrieval aims to find any bridge in a given dataset of images, whilst instance-level retrieval must find the Sydney Harbour bridge to be considered a match.

Source: Camera Obscurer: Generative Art for Design Inspiration

Papers

Showing 191195 of 195 papers

TitleStatusHype
Who's Afraid of Adversarial Queries? The Impact of Image Modifications on Content-based Image RetrievalCode0
Automatic Query Image Disambiguation for Content-Based Image RetrievalCode0
Saliency Map-based Image Retrieval using Invariant Krawtchouk MomentsCode0
Enhancing Flood Impact Analysis using Interactive Retrieval of Social Media ImagesCode0
Privacy Leakage of SIFT Features via Deep Generative Model based Image ReconstructionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1LHRRMAP90.94Unverified