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

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Showing 151–175 of 195 papers

TitleStatusHype
Texture Retrieval via the Scattering Transform—0
Medical Image Super-Resolution Using a Generative Adversarial Network—0
The Shortlist Method for Fast Computation of the Earth Mover's Distance and Finding Optimal Solutions to Transportation Problems—0
Towards Practical Visual Search Engine within Elasticsearch—0
Triagem virtual de imagens de imuno-histoquímica usando redes neurais artificiais e espectro de padrões—0
Unsupervised Multi-modal Hashing for Cross-modal retrieval—0
Unsupervised Content based Image Retrieval at Different Precision Level by Combining Multiple Features—0
VISIR: Visual and Semantic Image Label Refinement—0
Visual descriptors for content-based retrieval of remote sensing images—0
Visual Relationship Detection with Language Priors—0
Web image search engine based on LSH index and CNN Resnet50—0
Image Retrieval using Histogram Factorization and Contextual Similarity Learning—0
On Validation of Search & Retrieval of Tissue Images in Digital Pathology—0
A Bag of Visual Words Model for Medical Image Retrieval—0
Accurate and Fast Pixel Retrieval with Spatial and Uncertainty Aware Hypergraph Diffusion—0
A Genetic Algorithm Approach for ImageRepresentation Learning through Color Quantization—0
A Comparative Analysis of Retrieval Techniques In Content Based Image Retrieval—0
A Comparison of CNN and Classic Features for Image Retrieval—0
A Curated Image Parameter Dataset from Solar Dynamics Observatory Mission—0
A Decade Survey of Content Based Image Retrieval using Deep Learning—0
A Dense-Depth Representation for VLAD descriptors in Content-Based Image Retrieval—0
Advancements in Content-Based Image Retrieval: A Comprehensive Survey of Relevance Feedback Techniques—0
A Fast Content-Based Image Retrieval Method Using Deep Visual Features—0
Aggregating Binary Local Descriptors for Image Retrieval—0
A Hybrid Approach for Improved Content-based Image Retrieval using Segmentation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1LHRRMAP90.94—Unverified