Content-Based Image Retrieval
31 papers with code • 1 benchmarks • 5 datasets
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
Latest papers
Contextual Similarity Aggregation with Self-attention for Visual Re-ranking
Since our re-ranking model is not directly involved with the visual feature used in the initial retrieval, it is ready to be applied to retrieval result lists obtained from various retrieval algorithms.
iART: A Search Engine for Art-Historical Images to Support Research in the Humanities
In this paper, we introduce iART: an open Web platform for art-historical research that facilitates the process of comparative vision.
City-Scale Visual Place Recognition with Deep Local Features Based on Multi-Scale Ordered VLAD Pooling
In this paper, we present a fully-automated system for place recognition at a city-scale based on content-based image retrieval.
Privacy Leakage of SIFT Features via Deep Generative Model based Image Reconstruction
It is shown that, if the adversary can only have access to the SIFT descriptors while not their coordinates, then the modest success of reconstructing the latent image can be achieved for highly-structured images (e. g., faces) and would fail in general settings.
PyRetri: A PyTorch-based Library for Unsupervised Image Retrieval by Deep Convolutional Neural Networks
Despite significant progress of applying deep learning methods to the field of content-based image retrieval, there has not been a software library that covers these methods in a unified manner.
CBIR using features derived by Deep Learning
In a Content Based Image Retrieval (CBIR) System, the task is to retrieve similar images from a large database given a query image.
Multimedia Retrieval Through Unsupervised Hypergraph-Based Manifold Ranking
In this paper, a novel manifold ranking algorithm is proposed based on the hypergraphs for unsupervised multimedia retrieval tasks.
Enhancing Flood Impact Analysis using Interactive Retrieval of Social Media Images
The analysis of natural disasters such as floods in a timely manner often suffers from limited data due to a coarse distribution of sensors or sensor failures.
Semantic Hierarchy Preserving Deep Hashing for Large-scale Image Retrieval
Deep hashing models have been proposed as an efficient method for large-scale similarity search.
Who's Afraid of Adversarial Queries? The Impact of Image Modifications on Content-based Image Retrieval
An adversarial query is an image that has been modified to disrupt content-based image retrieval (CBIR) while appearing nearly untouched to the human eye.