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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

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Showing 26–50 of 195 papers

TitleStatusHype
Annotation Cost-Efficient Active Learning for Deep Metric Learning Driven Remote Sensing Image Retrieval—0
A Novel Framework to Jointly Compress and Index Remote Sensing Images for Efficient Content-Based Retrieval—0
A Privacy-Preserving Content-Based Image Retrieval Scheme Allowing Mixed Use Of Encrypted And Plain Images—0
A Privacy-Preserving Image Retrieval Scheme with a Mixture of Plain and EtC Images—0
A Revisit on Deep Hashings for Large-scale Content Based Image Retrieval—0
A Curated Image Parameter Dataset from Solar Dynamics Observatory Mission—0
Accurate and Fast Pixel Retrieval with Spatial and Uncertainty Aware Hypergraph Diffusion—0
Autoencoding the Retrieval Relevance of Medical Images—0
A unified framework of predicting binary interestingness of images based on discriminant correlation analysis and multiple kernel learning—0
Efficient Object Embedding for Spliced Image Retrieval—0
On Validation of Search & Retrieval of Tissue Images in Digital Pathology—0
Automatic Feature Weight Determination using Indexing and Pseudo-Relevance Feedback for Multi-feature Content-Based Image Retrieval—0
An Automatic Image Content Retrieval Method for better Mobile Device Display User Experiences—0
A Triplet-loss Dilated Residual Network for High-Resolution Representation Learning in Image Retrieval—0
Benchmarking unsupervised near-duplicate image detection—0
BigEarthNet Dataset with A New Class-Nomenclature for Remote Sensing Image Understanding—0
Binary Codes for Tagging X-Ray Images via Deep De-Noising Autoencoders—0
A Sub-block Based Image Retrieval Using Modified Integrated Region Matching—0
Bridging Gap between Image Pixels and Semantics via Supervision: A Survey—0
Bridging the Gap between Local Semantic Concepts and Bag of Visual Words for Natural Scene Image Retrieval—0
CBIDR: A novel method for information retrieval combining image and data by means of TOPSIS applied to medical diagnosis—0
A new Local Radon Descriptor for Content-Based Image Search—0
Challenging deep image descriptors for retrieval in heterogeneous iconographic collections—0
An Improved Relevance Feedback in CBIR—0
A Hybrid Approach for Improved Content-based Image Retrieval using Segmentation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1LHRRMAP90.94—Unverified