We develop an image similarity descriptor for an image pair, based on deep features. The development consists of two parts - selecting the deep layer whose features are to be included in the descriptor, and a representation of the similarity between the images in the pair. The selection of the deep layer follows a sparse representation of the feature maps followed by multi-output support vector regression. The similarity representation is based on a novel correlation between the histograms of the feature maps of the two images. Experiments to demonstrate the effectiveness of the proposed descriptor are carried out on four applications that can be cast as classification tasks
In this paper, we address the problem of pair-wise image matching which determines whether two image...
Sparse representation of signals has recently emerged as a major research area. It is well-known tha...
The paper addresses the issue of searching for similar images and objects ina repository of informat...
[[abstract]]Assessment of image similarity is fundamentally important to numerous multimedia applica...
Abstract The paper addresses the issue of searching for similar images and objects in a repository o...
This master´s thesis deals with the reseach of technologies using deep learning method, being able t...
The paper addresses the issue of searching for similar images and objects in arepository of informat...
Encoding an object essence in terms of self-similarities between its parts is becoming a popular str...
Kernel descriptors have been proven to outperform existing histogram based local descriptors as such...
Detection of keypoints from image and their characterization by using descriptors is common techniqu...
In computer vision, an object can be modeled in two main ways: by explicitly measuring its character...
International audienceComparing patches across images is probably one of the most fundamental tasks ...
. Image similarity can be defined in a number of different semantic contexts. At the lowest common d...
Adopting a measure is essential in many multimedia applications. Recently, distance learning is beco...
Feature matching in omnidirectional vision systems is a challenging problem, mainly because compli-c...
In this paper, we address the problem of pair-wise image matching which determines whether two image...
Sparse representation of signals has recently emerged as a major research area. It is well-known tha...
The paper addresses the issue of searching for similar images and objects ina repository of informat...
[[abstract]]Assessment of image similarity is fundamentally important to numerous multimedia applica...
Abstract The paper addresses the issue of searching for similar images and objects in a repository o...
This master´s thesis deals with the reseach of technologies using deep learning method, being able t...
The paper addresses the issue of searching for similar images and objects in arepository of informat...
Encoding an object essence in terms of self-similarities between its parts is becoming a popular str...
Kernel descriptors have been proven to outperform existing histogram based local descriptors as such...
Detection of keypoints from image and their characterization by using descriptors is common techniqu...
In computer vision, an object can be modeled in two main ways: by explicitly measuring its character...
International audienceComparing patches across images is probably one of the most fundamental tasks ...
. Image similarity can be defined in a number of different semantic contexts. At the lowest common d...
Adopting a measure is essential in many multimedia applications. Recently, distance learning is beco...
Feature matching in omnidirectional vision systems is a challenging problem, mainly because compli-c...
In this paper, we address the problem of pair-wise image matching which determines whether two image...
Sparse representation of signals has recently emerged as a major research area. It is well-known tha...
The paper addresses the issue of searching for similar images and objects ina repository of informat...