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Content-Based Image Retrieval

15 papers with code ยท Computer Vision
Subtask of 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

Benchmarks

You can find evaluation results in the subtasks. You can also submitting evaluation metrics for this task.

Latest papers without code

City-Scale Visual Place Recognition with Deep Local Features Based on Multi-Scale Ordered VLAD Pooling

19 Sep 2020

In this paper, we present a fully-automated system for place recognition at a city-scale based on content-based image retrieval.

CONTENT-BASED IMAGE RETRIEVAL VISUAL PLACE RECOGNITION

Neuromorphic Computing for Content-based Image Retrieval

4 Aug 2020

Neuromorphic computing mimics the neural activity of the brain through emulating spiking neural networks.

CONTENT-BASED IMAGE RETRIEVAL RECOMMENDATION SYSTEMS

A new Local Radon Descriptor for Content-Based Image Search

30 Jul 2020

Content-based image retrieval (CBIR) is an essential part of computer vision research, especially in medical expert systems.

CONTENT-BASED IMAGE RETRIEVAL

A Bag of Visual Words Model for Medical Image Retrieval

18 Jul 2020

Medical Image Retrieval is a challenging field in Visual information retrieval, due to the multi-dimensional and multi-modal context of the underlying content.

CONTENT-BASED IMAGE RETRIEVAL IMAGE CLASSIFICATION INFORMATION RETRIEVAL MEDICAL IMAGE RETRIEVAL

A new approach to descriptors generation for image retrieval by analyzing activations of deep neural network layers

13 Jul 2020

The idea of neural codes, based on fully connected layers activations, is extended by incorporating the information contained in convolutional layers.

CONTENT-BASED IMAGE RETRIEVAL

Nodule2vec: a 3D Deep Learning System for Pulmonary Nodule Retrieval Using Semantic Representation

11 Jul 2020

Content-based retrieval supports a radiologist decision making process by presenting the doctor the most similar cases from the database containing both historical diagnosis and further disease development history.

CONTENT-BASED IMAGE RETRIEVAL DECISION MAKING LUNG NODULE DETECTION TRANSFER LEARNING

An Improved Relevance Feedback in CBIR

21 Jun 2020

This paper shows a novel addition to the prior methods to further improve the retrieval accuracy.

CONTENT-BASED IMAGE RETRIEVAL

Rotation Invariant Deep CBIR

21 Jun 2020

But the CNN features, being rotation invariant, creates problems to build a rotation-invariant CBIR system.

CONTENT-BASED IMAGE RETRIEVAL

Semi-supervised lung nodule retrieval

4 May 2020

However, in a previous study, we have shown that binary auxiliary tasks are inferior to the usage of a rough similarity estimate that are derived from data annotations.

CONTENT-BASED IMAGE RETRIEVAL DECISION MAKING SEMANTIC SIMILARITY SEMANTIC TEXTUAL SIMILARITY

CBIR using features derived by Deep Learning

13 Feb 2020

In a Content Based Image Retrieval (CBIR) System, the task is to retrieve similar images from a large database given a query image.

CONTENT-BASED IMAGE RETRIEVAL IMAGE CLASSIFICATION