Image retrieval
View article: Deep Hashing Network for Efficient Similarity Retrieval
Deep Hashing Network for Efficient Similarity Retrieval Open
Due to the storage and retrieval efficiency, hashing has been widely deployed to approximate nearest neighbor search for large-scale multimedia retrieval. Supervised hashing, which improves the quality of hash coding by exploiting the sema…
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The sketchy database Open
We present the Sketchy database , the first large-scale collection of sketch-photo pairs. We ask crowd workers to sketch particular photographic objects sampled from 125 categories and acquire 75,471 sketches of 12,500 objects. The Sketchy…
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V0.1IC Open
Hamming Cube, a deep learning framework that jointly learns compact binary codes and continuous embeddings while preserving Hamming distance structure.
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Sketch Me That Shoe Open
This project received support from the European Union’s Horizon 2020 research and innovation programme under grant agreement #640891, the Royal Society and Natural Science Foundation of China (NSFC) joint grant #IE141387 and #61511130081, …
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Fine-Tuning Convolutional Neural Networks for Biomedical Image Analysis: Actively and Incrementally Open
Intense interest in applying convolutional neural networks (CNNs) in biomedical image analysis is wide spread, but its success is impeded by the lack of large annotated datasets in biomedical imaging. Annotating biomedical images is not on…
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Content‐Based Image Retrieval and Feature Extraction: A Comprehensive Review Open
Multimedia content analysis is applied in different real‐world computer vision applications, and digital images constitute a major part of multimedia data. In last few years, the complexity of multimedia contents, especially the images, ha…
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Automated Detection and Classification of Oral Lesions Using Deep Learning for Early Detection of Oral Cancer Open
Oral cancer is a major global health issue accounting for 177,384 deaths in 2018 and it is most prevalent in low- and middle-income countries. Enabling automation in the identification of potentially malignant and malignant lesions in the …
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A Decade Survey of Content Based Image Retrieval Using Deep Learning Open
The content based image retrieval aims to find the similar images from a\nlarge scale dataset against a query image. Generally, the similarity between\nthe representative features of the query image and dataset images is used to\nrank the …
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[Paper] Visual Instance Retrieval with Deep Convolutional Networks Open
This paper provides an extensive study on the availability of image representations based on convolutional networks (ConvNets) for the task of visual instance retrieval. Besides the choice of convolutional layers, we present an efficient p…
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Retrieval of Brain Tumors by Adaptive Spatial Pooling and Fisher Vector Representation Open
Content-based image retrieval (CBIR) techniques have currently gained increasing popularity in the medical field because they can use numerous and valuable archived images to support clinical decisions. In this paper, we concentrate on dev…
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Deep Visual-Semantic Hashing for Cross-Modal Retrieval Open
Due to the storage and retrieval effciency, hashing has been widely applied to approximate nearest neighbor search for large-scale multimedia retrieval. Cross-modal hashing, which enables effcient retrieval of images in response to text qu…
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Deep Spatial-Semantic Attention for Fine-Grained Sketch-Based Image Retrieval Open
Human sketches are unique in being able to capture both the spatial topology of a visual object, as well as its subtle appearance details. Fine-grained sketch-based image retrieval (FG-SBIR) importantly leverages on such fine-grained chara…
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Content-Based Brain Tumor Retrieval for MR Images Using Transfer Learning Open
This paper presents an automatic content-based image retrieval (CBIR) system for brain tumors on T1-weighted contrast-enhanced magnetic resonance images (CE-MRI). The key challenge in CBIR systems for MR images is the semantic gap between …
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Deep Quantization Network for Efficient Image Retrieval Open
Hashing has been widely applied to approximate nearest neighbor search for large-scale multimedia retrieval. Supervised hashing improves the quality of hash coding by exploiting the semantic similarity on data pairs and has received increa…
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Wireless Image Retrieval at the Edge Open
We study the image retrieval problem at the wireless edge, where an edge device captures an image, which is then used to retrieve similar images from an edge server. These can be images of the same person or a vehicle taken from other came…
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BIIGLE 2.0 - Browsing and Annotating Large Marine Image Collections Open
Combining state-of-the art digital imaging technology with different kinds of marine exploration techniques such as modern AUV (autonomous underwater vehicle), ROV (remote operating vehicle) or other monitoring platforms enables marine ima…
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Multilabel Remote Sensing Image Retrieval Based on Fully Convolutional Network Open
Conventional remote sensing image retrieval (RSIR) systems usually perform single-label retrieval where each image is annotated by a single label representing the most significant semantic content of the image. This assumption, however, ig…
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Beyond Part Models: Person Retrieval with Refined Part Pooling. Open
Employing part-level features for pedestrian image description offers fine-grained information and has been verified as beneficial for person retrieval in very recent literature. A prerequisite of part discovery is that each part should be…
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Fine-Tuning CNN Image Retrieval with No Human Annotation Open
Image 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. Training of CNNs, either from s…
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Effective Multi-Query Expansions: Collaborative Deep Networks for Robust Landmark Retrieval Open
Given a query photo issued by a user (q-user), the landmark retrieval is to return a set of photos with their landmarks similar to those of the query, while the existing studies on the landmark retrieval focus on exploiting geometries of l…
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Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval Open
Remote sensing (RS) cross-modal text-image retrieval has attracted extensive attention for its advantages of flexible input and efficient query. However, traditional methods ignore the characteristics of multi-scale and redundant targets i…
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Efficient Diffusion on Region Manifolds: Recovering Small Objects with Compact CNN Representations Open
Query expansion is a popular method to improve the quality of image retrieval\nwith both conventional and CNN representations. It has been so far limited to\nglobal image similarity. This work focuses on diffusion, a mechanism that\ncaptur…
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Binary Generative Adversarial Networks for Image Retrieval Open
The most striking successes in image retrieval using deep hashing have mostly involved discriminative models, which require labels. In this paper, we use binary generative adversarial networks (BGAN) to embed images to binary codes in an u…
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Deep Supervised Discrete Hashing Open
With the rapid growth of image and video data on the web, hashing has been extensively studied for image or video search in recent years. Benefit from recent advances in deep learning, deep hashing methods have achieved promising results f…
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Precise Zero-Shot Dense Retrieval without Relevance Labels Open
While dense retrieval has been shown to be effective and efficient across tasks and languages, it remains difficult to create effective fully zero-shot dense retrieval systems when no relevance labels are available. In this paper, we recog…
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Deep Learning for Instance Retrieval: A Survey Open
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 content creation and sharing has introduced new challenges, pa…
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Recent Advance in Content-based Image Retrieval: A Literature Survey Open
The explosive increase and ubiquitous accessibility of visual data on the Web have led to the prosperity of research activity in image search or retrieval. With the ignorance of visual content as a ranking clue, methods with text search te…
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SSDH: Semi-Supervised Deep Hashing for Large Scale Image Retrieval Open
Hashing methods have been widely used for efficient similarity retrieval on\nlarge scale image database. Traditional hashing methods learn hash functions to\ngenerate binary codes from hand-crafted features, which achieve limited\naccuracy…
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Bags of Local Convolutional Features for Scalable Instance Search Open
This work proposes a simple instance retrieval pipeline based on encoding the\nconvolutional features of CNN using the bag of words aggregation scheme (BoW).\nAssigning each local array of activations in a convolutional layer to a visual\n…
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Remote Sensing Cross-Modal Text-Image Retrieval Based on Global and Local Information Open
Cross-modal remote sensing text-image retrieval (RSCTIR) has recently become\nan urgent research hotspot due to its ability of enabling fast and flexible\ninformation extraction on remote sensing (RS) images. However, current RSCTIR\nmetho…