Content-Based Image Retrieval
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Benchmarks
INRIA Holidays Dataset
Most implemented
A clinically motivated self-supervised approach for content-based image retrieval of CT liver images
Conditioned and Composed Image Retrieval Combining and Partially Fine-Tuning CLIP-Based Features
GPR1200: A Benchmark for General-Purpose Content-Based Image Retrieval
Classification is a Strong Baseline for Deep Metric Learning
Dual-Path Convolutional Image-Text Embeddings with Instance Loss
Content-based image retrieval tutorial
Papers
Training-Free Pseudo-Fusion for Composed Image Retrieval with Diffusion Models and Multimodal Large Language Models
Composed Image Retrieval (CIR) is an emerging paradigm in content-based image retrieval that enables users to formulate compositional queries by combining a reference image with an auxiliary modality, usually text-based.…
Content-Based Image RetrievalGeometric Analysis of Self-Supervised Vision Representations for Semantic Image Retrieval
Content-based image retrieval (CBIR) systems enable users to search images based on visual content instead of relying on metadata. The text domain has benefited from vector search of representations created with unsuperv…
Content-Based Image RetrievalSelf-Supervised LearningSemantic RetrievalEvaluating the Impact of Data Anonymization on Image Retrieval
With the growing importance of privacy regulations such as the General Data Protection Regulation, anonymizing visual data is becoming increasingly relevant across institutions. However, anonymization can negatively affe…
Content-Based Image RetrievalToward a Universal Color Naming System: A Clustering-Based Approach using Multisource Data
Is it coral, salmon, or peach? What seems like a simple color can have many names, and without a standard, these variations create confusion across design, technology, and communication. Color naming is a fundamental tas…
Content-Based Image RetrievalAcquisition of interpretable domain information during brain MR image harmonization for content-based image retrieval
Medical images like MR scans often show domain shifts across imaging sites due to scanner and protocol differences, which degrade machine learning performance in tasks such as disease classification. Domain harmonization…
Content-Based Image RetrievalRepresentation LearningImage ReconstructionImage HarmonizationCSMoE: An Efficient Remote Sensing Foundation Model with Soft Mixture-of-Experts
Self-supervised learning (SSL) through masked autoencoders (MAEs) has recently attracted great attention for remote sensing (RS) foundation model (FM) development, enabling improved representation learning across diverse…
Content-Based Image RetrievalSelf-Supervised LearningComputational EfficiencyRepresentation Learning