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ACM Computing Surveys, 2008
We have witnessed great interest and a wealth of promise in content-based image retrieval as an emerging technology. While the last decade laid foundation to such promise, it also paved the way for a large number of new techniques and systems, got many new people involved, and triggered stronger association of weakly related fields. In this article, we
Ritendra Datta, Dhiraj Joshi, Jia Li
exaly +3 more sources
We have witnessed great interest and a wealth of promise in content-based image retrieval as an emerging technology. While the last decade laid foundation to such promise, it also paved the way for a large number of new techniques and systems, got many new people involved, and triggered stronger association of weakly related fields. In this article, we
Ritendra Datta, Dhiraj Joshi, Jia Li
exaly +3 more sources
CoSMo: Content-Style Modulation for Image Retrieval with Text Feedback
Computer Vision and Pattern Recognition, 2021We tackle the task of image retrieval with text feedback, where a reference image and modifier text are combined to identify the desired target image.
Seung-Min Lee, Dongwan Kim, Bohyung Han
semanticscholar +1 more source
A Lightweight Multi-Scale Crossmodal Text-Image Retrieval Method in Remote Sensing
IEEE Transactions on Geoscience and Remote Sensing, 2022Remote sensing (RS) crossmodal text-image retrieval has become a research hotspot in recent years for its application in semantic localization. However, since multiple inferences on slices are demanded in semantic localization, designing a crossmodal ...
Zhiqiang Yuan +7 more
semanticscholar +1 more source
Deep Fuzzy Hashing Network for Efficient Image Retrieval
IEEE transactions on fuzzy systems, 2021Hashing 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 preserved.
Huimin Lu +4 more
semanticscholar +1 more source
On the Unreasonable Effectiveness of Centroids in Image Retrieval
International Conference on Neural Information Processing, 2021Image retrieval task consists of finding similar images to a query image from a set of gallery (database) images. Such systems are used in various applications e.g. person re-identification (ReID) or visual product search.
Mikolaj Wieczorek +2 more
semanticscholar +1 more source
Comprehensive Linguistic-Visual Composition Network for Image Retrieval
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021Composing text and image for image retrieval (CTI-IR) is a new yet challenging task, for which the input query is not the conventional image or text but a composition, i.e., a reference image and its corresponding modification text.
Haokun Wen +4 more
semanticscholar +1 more source
2009 16th IEEE International Conference on Image Processing (ICIP), 2009
The paper presents a method for content-based image retrieval based on an evolutionary algorithm. Stochastic approaches have been applied with success in several optimization problems thanks to their capability to explore the solution space, in particular in complex, multidimensional spaces, avoiding local maxima of the target function.
Broilo, Mattia, De Natale, Francesco
openaire +2 more sources
The paper presents a method for content-based image retrieval based on an evolutionary algorithm. Stochastic approaches have been applied with success in several optimization problems thanks to their capability to explore the solution space, in particular in complex, multidimensional spaces, avoiding local maxima of the target function.
Broilo, Mattia, De Natale, Francesco
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Deep Transfer Hashing for Image Retrieval
IEEE transactions on circuits and systems for video technology (Print), 2021Deep supervised hashing has emerged as an influential solution to large-scale semantic image retrieval problems in computer vision. In the light of recent progress, image label is the common way to define whether two images belong to the same category ...
Hongjia Zhai +4 more
semanticscholar +1 more source
Fine-Tuning CNN Image Retrieval with No Human Annotation
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017Image descriptors based on activations of Convolutional Neural Networks (CNNs) have become dominant in image retrieval due to their discriminative power, compactness of representation, and search efficiency.
Filip Radenovic +2 more
semanticscholar +1 more source
Localized content based image retrieval
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval, 2005We define localized content-based image retrieval as a CBIR task where the user is only interested in a portion of the image, and the rest of the image is irrelevant. In this paper we present a localized CBIR system, Accio, that uses labeled images in conjunction with a multiple-instance learning algorithm to first identify the desired object and ...
Rouhollah, Rahmani +4 more
openaire +2 more sources