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 181190 of 195 papers

TitleStatusHype
PinView: Implicit Feedback in Content-Based Image Retrieval0
Image Retrieval And Classification Using Local Feature Vectors0
The Shortlist Method for Fast Computation of the Earth Mover's Distance and Finding Optimal Solutions to Transportation Problems0
Image Annotation with ISO-Space: Distinguishing Content from Structure0
Large-margin Learning of Compact Binary Image Encodings0
Pareto-depth for Multiple-query Image Retrieval0
Survey on Sparse Coded Features for Content Based Face Image Retrieval0
Content Based Image Indexing and Retrieval0
Content Based Image Retrieval System using Feature Classification with Modified KNN Algorithm0
A Sub-block Based Image Retrieval Using Modified Integrated Region Matching0
Show:102550
← PrevPage 19 of 20Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1LHRRMAP90.94Unverified