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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–75 of 195 papers

TitleStatusHype
Class Anchor Margin Loss for Content-Based Image Retrieval—0
Classifying magnetic resonance image modalities with convolutional neural networks—0
Class-Specific Variational Auto-Encoder for Content-Based Image Retrieval—0
Color Image Retrieval Using Fuzzy Measure Hamming and S-Tree—0
Combining Real-Valued and Binary Gabor-Radon Features for Classification and Search in Medical Imaging Archives—0
Comparative Study and Optimization of Feature-Extraction Techniques for Content based Image Retrieval—0
Computing Similarity between Cultural Heritage Items using Multimodal Features—0
A Bag of Visual Words Model for Medical Image Retrieval—0
Constrained Mass Optimal Transport—0
Content-Based Brain Tumor Retrieval for MR Images Using Transfer Learning—0
Content Based Image Indexing and Retrieval—0
Content-based Image Retrieval and the Semantic Gap in the Deep Learning Era—0
CBIDR: A novel method for information retrieval combining image and data by means of TOPSIS applied to medical diagnosis—0
Bridging the Gap between Local Semantic Concepts and Bag of Visual Words for Natural Scene Image Retrieval—0
A new approach to descriptors generation for image retrieval by analyzing activations of deep neural network layers—0
Bridging Gap between Image Pixels and Semantics via Supervision: A Survey—0
BOSS: Bottom-up Cross-modal Semantic Composition with Hybrid Counterfactual Training for Robust Content-based Image Retrieval—0
An Efficient Image Retrieval Based on Fusion of Low-Level Visual Features—0
Binary Codes for Tagging X-Ray Images via Deep De-Noising Autoencoders—0
BigEarthNet Dataset with A New Class-Nomenclature for Remote Sensing Image Understanding—0
An Efficient Framework for Zero-Shot Sketch-Based Image Retrieval—0
Benchmarking unsupervised near-duplicate image detection—0
Automatic tagging and retrieval of E-Commerce products based on visual features—0
An Effective Automatic Image Annotation Model Via Attention Model and Data Equilibrium—0
A Curated Image Parameter Dataset from Solar Dynamics Observatory Mission—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1LHRRMAP90.94—Unverified