Deep learning for instance retrieval: A survey
In recent years a vast amount of visual content has been generated and shared from many
fields, such as social media platforms, medical imaging, and robotics. This abundance of …
fields, such as social media platforms, medical imaging, and robotics. This abundance of …
SIFT meets CNN: A decade survey of instance retrieval
In the early days, content-based image retrieval (CBIR) was studied with global features.
Since 2003, image retrieval based on local descriptors (de facto SIFT) has been extensively …
Since 2003, image retrieval based on local descriptors (de facto SIFT) has been extensively …
Deep fuzzy hashing network for efficient image retrieval
Hashing methods for efficient image retrieval aim at learning hash functions that map similar
images to semantically correlated binary codes in the Hamming space with similarity well …
images to semantically correlated binary codes in the Hamming space with similarity well …
A decade survey of content based image retrieval using deep learning
SR Dubey - IEEE Transactions on Circuits and Systems for …, 2021 - ieeexplore.ieee.org
The content based image retrieval aims to find the similar images from a large scale dataset
against a query image. Generally, the similarity between the representative features of the …
against a query image. Generally, the similarity between the representative features of the …
Person re-identification: Past, present and future
Person re-identification (re-ID) has become increasingly popular in the community due to its
application and research significance. It aims at spotting a person of interest in other …
application and research significance. It aims at spotting a person of interest in other …
Hashnet: Deep learning to hash by continuation
Learning to hash has been widely applied to approximate nearest neighbor search for large-
scale multimedia retrieval, due to its computation efficiency and retrieval quality. Deep …
scale multimedia retrieval, due to its computation efficiency and retrieval quality. Deep …
Deep supervised hashing for fast image retrieval
In this paper, we present a new hashing method to learn compact binary codes for highly
efficient image retrieval on large-scale datasets. While the complex image appearance …
efficient image retrieval on large-scale datasets. While the complex image appearance …
Deep cross-modal hashing
Due to its low storage cost and fast query speed, cross-modal hashing (CMH) has been
widely used for similarity search in multimedia retrieval applications. However, most existing …
widely used for similarity search in multimedia retrieval applications. However, most existing …
A survey on learning to hash
Nearest neighbor search is a problem of finding the data points from the database such that
the distances from them to the query point are the smallest. Learning to hash is one of the …
the distances from them to the query point are the smallest. Learning to hash is one of the …
Feature learning based deep supervised hashing with pairwise labels
Recent years have witnessed wide application of hashing for large-scale image retrieval.
However, most existing hashing methods are based on hand-crafted features which might …
However, most existing hashing methods are based on hand-crafted features which might …