Content-Based Image Retrieval Edit Task
Computer Vision • Image Retrieval
About
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
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Subtasks
Datasets
Greatest papers with code
PyRetri: A PyTorch-based Library for Unsupervised Image Retrieval by Deep Convolutional Neural Networks
• PyRetri/PyRetri
• 
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.
Dual-Path Convolutional Image-Text Embedding with Instance Loss
In this paper, we propose a new system to discriminatively embed the image and text to a shared visual-textual space.
Ranked #1 on
NLP based Person Retrival
on CUHK-PEDES
(R@1 metric)
CONTENT-BASED IMAGE RETRIEVAL CROSS-MODAL RETRIEVAL NLP BASED PERSON RETRIVAL PERSON RETRIEVAL TEXT BASED PERSON RETRIEVAL TEXT-IMAGE RETRIEVAL
Classification is a Strong Baseline for Deep Metric Learning
Deep metric learning aims to learn a function mapping image pixels to embedding feature vectors that model the similarity between images.
Ranked #3 on
Image Retrieval
on CARS196
BINARIZATION CONTENT-BASED IMAGE RETRIEVAL FACE VERIFICATION METRIC LEARNING
Content-based image retrieval tutorial
This paper functions as a tutorial for individuals interested to enter the field of information retrieval but wouldn't know where to begin from.
Socializing the Semantic Gap: A Comparative Survey on Image Tag Assignment, Refinement and Retrieval
Where previous reviews on content-based image retrieval emphasize on what can be seen in an image to bridge the semantic gap, this survey considers what people tag about an 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.
Who's Afraid of Adversarial Queries? The Impact of Image Modifications on Content-based Image Retrieval
• liuzrcc/PIRE
•
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.
Automatic Query Image Disambiguation for Content-Based Image Retrieval
Query images presented to content-based image retrieval systems often have various different interpretations, making it difficult to identify the search objective pursued by the user.
Information-Theoretic Active Learning for Content-Based Image Retrieval
We propose Information-Theoretic Active Learning (ITAL), a novel batch-mode active learning method for binary classification, and apply it for acquiring meaningful user feedback in the context of content-based image retrieval.