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Unsupervised graph-based rank aggregation for improved retrieval

Icaro Cavalcante Dourado, Daniel Carlos Guimarães Pedronette, Ricardo da Silva Torres
2019 Information Processing & Management  
on a unified graph-based model of rank fusions.  ...  We reformulate the ad-hoc retrieval problem as a document retrieval based on fusion graphs, which we propose as a new unified representation model capable of merging multiple ranks and expressing inter-relationships  ...  In this paper, we propose an unsupervised graph-based rank aggregation method, agnostic of the rankers being fused, and targeted for general applicability, such as image, textual, or even multimodal retrieval  ... 
doi:10.1016/j.ipm.2019.03.008 fatcat:v2whndfz3zcj7g3ci4sk3cbyde

Multimodal Prediction based on Graph Representations [article]

Icaro Cavalcante Dourado, Salvatore Tabbone, Ricardo da Silva Torres
2020 arXiv   pre-print
This paper proposes a learning model, based on rank-fusion graphs, for general applicability in multimodal prediction tasks, such as multimodal regression and image classification.  ...  The solution is based on the encoding of multiple ranks for a query (or test sample), defined according to different criteria, into a graph.  ...  Conclusions This paper presented an unsupervised graph-based rank-fusion approach as a representation model for multimodal prediction tasks.  ... 
arXiv:1912.10314v4 fatcat:jyj62akpabhj3jjkyl4ovn5dpy

Image Re-ranking using Information Gain and Relative Consistency through Multi-graph Learning

Poonam N., Supriya A.
2016 International Journal of Computer Applications  
After receiving a lot of attention towards text based searching for image retrieval, researchers have focused on content based image retrieval.  ...  Visual re-ranking is a method of image retrieval, which has been widely accepted to boost the accuracy of traditional text-based image retrieval.  ...  We present a submodular graph based technique for re-ranking images retrieved by multiple feature channels, which is fully unsupervised.  ... 
doi:10.5120/ijca2016911131 fatcat:cenvennv2repxgtpsikmwsgjse

Visual Reranking through Weakly Supervised Multi-graph Learning

Cheng Deng, Rongrong Ji, Wei Liu, Dacheng Tao, Xinbo Gao
2013 2013 IEEE International Conference on Computer Vision  
Visual reranking has been widely deployed to refine the quality of conventional content-based image retrieval engines.  ...  Meanwhile, such learning can yield a few anchors in graphs that vitally enable the alignment and fusion of multiple graphs.  ...  Given the mined attributes, we then select A images with the maximum responses as the anchors for graph alignment and fusion in Section 3.  ... 
doi:10.1109/iccv.2013.323 dblp:conf/iccv/DengJLTG13 fatcat:snnwxxwwfffklgvcwmz7prkntq

Unsupervised manifold learning through reciprocal kNN graph and Connected Components for image retrieval tasks

Daniel Carlos Guimarães Pedronette, Filipe Marcel Fernandes Gonçalves, Ivan Rizzo Guilherme
2018 Pattern Recognition  
This paper proposes a novel manifold learning approach that exploits the intrinsic dataset geometry for improving the effectiveness of image retrieval tasks.  ...  The method computes the new retrieval results on an unsupervised way, without the need of any user intervention.  ...  Acknowledgments The authors are grateful to FAPESP -São Paulo Research Foundation (grant # 2013/08645-0 ) and CAPES -Coordination for Higher Education Staff Development.  ... 
doi:10.1016/j.patcog.2017.05.009 fatcat:wdojfu33brf5zbzm6kzboms4ru

Three Tiers Neighborhood Graph and Multi-graph Fusion Ranking for Multi-feature Image Retrieval: A Manifold Aspect [article]

Shenglan Liu, Muxin Sun, Lin Feng, Yang Liu, Jun Wu
2016 arXiv   pre-print
Furthermore, we propose Multi-graph Fusion Ranking (MFR) for multi-feature ranking, which considers the correlation of all images in multiple neighborhood graphs.  ...  Multi-feature fusion ranking can be utilized to improve the ranking list of query. In this paper, we first analyze graph structure and multi-feature fusion re-ranking from manifold aspect.  ...  In this paper, we proposed a novel approach for image unsupervised re-ranking of single feature on graph and illustrated rationality of multi-graph fusion ranking by using probability theory.  ... 
arXiv:1609.07599v1 fatcat:rfeqoj7yrneklfyfu5kgbi2xk4

Query Adaptive Late Fusion for Image Retrieval [article]

Zhongdao Wang, Liang Zheng, Shengjin Wang
2018 arXiv   pre-print
Feature fusion is a commonly used strategy in image retrieval tasks, which aggregates the matching responses of multiple visual features.  ...  As such, this paper introduces a query-adaptive late fusion pipeline. In the hand-crafted version, it can be an unsupervised approach to tasks like particular object retrieval.  ...  Specifically, for unsupervised tasks such as particular image retrieval, we propose an unsupervised fusion scheme (QAF); for supervised tasks such as person recognition, we proposed a supervised method  ... 
arXiv:1810.13103v1 fatcat:3rvbbzxgg5cvbmmvz4ar3jlsmq

Semantic Guided Interactive Image Retrieval for plant identification

Filipe Marcel Fernandes Gonçalves, Ivan Rizzo Guilherme, Daniel Carlos Guimarães Pedronette
2018 Expert systems with applications  
This work proposes a novel graph-based approach denominated Semantic Interactive Image Retrieval (SIIR) capable of combining Content Based Image Retrieval (CBIR), unsupervised learning, ontology techniques  ...  A novel graph-based approach is proposed for combining the semantic information and the visual retrieval results.  ...  Acknowledgments The authors are grateful to CAPES (Coordination for Higher Education Staff Development), and São Paulo Research Foundation -FAPESP (Grant 2013/08645-0 ).  ... 
doi:10.1016/j.eswa.2017.08.035 fatcat:3hvxenhhefgplo4ppszlsc77va

2020 Index IEEE Transactions on Image Processing Vol. 29

2020 IEEE Transactions on Image Processing  
., +, TIP 2020 2439-2451 Graph-Based Non-Convex Low-Rank Regularization for Image Compression Artifact Reduction. Mu, J., +, TIP 2020 5374-5385 Graph-Based Transforms for Video Coding.  ...  ., +, TIP 2020 419-432 Graph-Based Non-Convex Low-Rank Regularization for Image Compres- sion Artifact Reduction.  ... 
doi:10.1109/tip.2020.3046056 fatcat:24m6k2elprf2nfmucbjzhvzk3m

Special issue on "visual semantic analysis with weak supervision"

Luming Zhang, Yang Yang, Rongrong Ji, Roger Zimmermann
2017 Multimedia Systems  
1 National University of Singapore, Singapore, Singapore Acknowledgments We also thank the reviewers for their efforts to guarantee the high quality of this special issue.  ...  These papers cover wide applications based on weakly supervised graph inference, weakly supervised feature selection, image retrieval using weak labels, and so on.  ...  In "Tag Relevance Fusion for Social Image Retrieval", Li et al. presented a systematic study, covering tag relevance fusion in the early and late stages, and in supervised and unsupervised settings.  ... 
doi:10.1007/s00530-016-0527-4 fatcat:72hcjiiwfzbk7mdrsumuia7rzy

Query Specific Fusion for Image Retrieval [chapter]

Shaoting Zhang, Ming Yang, Timothee Cour, Kai Yu, Dimitris N. Metaxas
2012 Lecture Notes in Computer Science  
Thus, we propose a graph-based query specific fusion approach where multiple retrieval sets are merged and reranked by conducting a link analysis on a fused graph.  ...  Recent image retrieval algorithms based on local features indexed by a vocabulary tree and holistic features indexed by compact hashing codes both demonstrate excellent scalability.  ...  The main contribution of the proposed approach is on the unsupervised graph-based fusion of retrieval sets given by different methods, which has three merits: 1) the retrieval quality specific to one query  ... 
doi:10.1007/978-3-642-33709-3_47 fatcat:yfv4moo4ubejxoauin4htot5wa

A hybrid graph-based and non-linear late fusion approach for multimedia retrieval

Ilias Gialampoukidis, Anastasia Moumtzidou, Dimitris Liparas, Stefanos Vrochidis, Ioannis Kompatsiaris
2016 2016 14th International Workshop on Content-Based Multimedia Indexing (CBMI)  
The fusion of multiple modalities for retrieval in an unsupervised way has been mostly based on early, weighted linear, graph-based and diffusion-based techniques.  ...  In contrast, we present a strategy for fusing textual and visual modalities, through the combination of a non-linear fusion model and a graph-based late fusion approach.  ...  A hybrid graph-based and non-linear late fusion model for multimedia retrieval.  ... 
doi:10.1109/cbmi.2016.7500252 dblp:conf/cbmi/GialampoukidisM16 fatcat:gggu5spoufduxbycflomf5b7vu

Tag relevance fusion for social image retrieval

Xirong Li
2014 Multimedia Systems  
Experiments on a large present-day benchmark set show that tag relevance fusion leads to better image retrieval.  ...  Due to the subjective nature of social tagging, measuring the relevance of social tags with respect to the visual content is crucial for retrieving the increasing amounts of social-networked images.  ...  Marcel Worring for their comments and suggestions on this work.  ... 
doi:10.1007/s00530-014-0430-9 fatcat:5z36n5pbjffmjc2aw3n3bamx5u

Graph based multi-modality learning

Hanghang Tong, Jingrui He, Mingjing Li, Changshui Zhang, Wei-Ying Ma
2005 Proceedings of the 13th annual ACM international conference on Multimedia - MULTIMEDIA '05  
For semi-supervised learning, two different fusion schemes, namely linear form and sequential form, are proposed.  ...  in every graph as well as supervision information (if available).  ...  For semi-supervised learning task, the authors in [10] applied a recent developed manifold ranking algorithm in content based image retrieval (CBIR) in the scenario of query by example (QBE).  ... 
doi:10.1145/1101149.1101337 dblp:conf/mm/TongHLZM05 fatcat:ux2tzibo6nbfrhr3pca2hxme6m

Deep Learning for Instance Retrieval: A Survey [article]

Wei Chen, Yu Liu, Weiping Wang, Erwin Bakker, Theodoros Georgiou, Paul Fieguth, Li Liu, Michael S. Lew
2022 arXiv   pre-print
This abundance of content creation and sharing has introduced new challenges, particularly that of searching databases for similar content-Content Based Image Retrieval (CBIR)-a long-established research  ...  area in which improved efficiency and accuracy are needed for real-time retrieval.  ...  ACKNOWLEDGMENT The authors would like to thank the pioneer researchers in instance retrieval and other related fields.  ... 
arXiv:2101.11282v3 fatcat:qvodunmw4bdltcneadyt7d7h5m
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