Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/2671188.2749318acmconferencesArticle/Chapter ViewAbstractPublication PagesicmrConference Proceedingsconference-collections
short-paper

Rapid Clothing Retrieval via Deep Learning of Binary Codes and Hierarchical Search

Published: 22 June 2015 Publication History

Abstract

This paper deals with the problem of clothing retrieval in a recommendation system. We develop a hierarchical deep search framework to tackle this problem. We use a pre-trained network model that has learned rich mid-level visual representations in module 1. Then, in module 2, we add a latent layer to the network and have neurons in this layer to learn hashes-like representations while fine-tuning it on the clothing dataset. Finally, module 3 achieves fast clothing retrieval using the learned hash codes and representations via a coarse-to-fine strategy. We use a large clothing dataset where 161,234 clothes images are collected and labeled. Experiments demonstrate the potential of our proposed framework for clothing retrieval in a large corpus.

References

[1]
T. Ahonen, A. Hadid, and M. Pietikainen. Face description with local binary patterns: Application to face recognition. IEEE Trans. PAMI, 28(12):2037--2041, 2006.
[2]
H. Chen, A. Gallagher, and B. Girod. Describing clothing by semantic attributes. In Proc. ECCV, 2012.
[3]
D. C. Ciresan, U. Meier, and J. Schmidhuber. Multi-column deep neural networks for image classification. In Proc. CVPR, 2012.
[4]
N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In Proc. CVPR, 2005.
[5]
M. Datar, N. Immorlica, P. Indyk, and V. Mirrokni. Locality-sensitive hashing scheme based on p-stable distributions. In Proc. SCG, 2004.
[6]
W. Di, C. Wah, A. Bhardwaj, R. Piramuthu, and N. Sundaresan. Style finder: Fine-grained clothing style detection and retrieval. In Proc. CVPR Workshops, 2013.
[7]
J. Donahue, Y. Jia, O. Vinyals, J. Hoffman, N. Zhang, E. Tzeng, and T. Darrell. DeCAF: A deep convolutional activation feature for generic visual recognition. In Proc. ICML, 2014.
[8]
P. F. Felzenszwalb, R. B. Girshick, D. McAllester, and D. Ramanan. Object detection with discriminatively trained part based models. IEEE Trans. PAMI, 32(9):1627--1645, 2010.
[9]
R. Girshick, J. Donahue, T. Darrell, and J. Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. In Proc. CVPR, 2014.
[10]
J. Huang, W. Xia, and S. Yan. Deep search with attribute-aware deep network. In Proc. ACM MM, 2014.
[11]
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell. Caffe: Convolutional architecture for fast feature embedding. arXiv preprint arXiv:1408.5093, 2014.
[12]
A. Krizhevsky, I. Sutskever, and G. E. Hinton. ImageNet classification with deep convolutional neural networks. In Proc. NIPS, 2012.
[13]
S. Liu, J. Feng, C. Domokos, H. Xu, J. Huang, Z. Hu, and S. Yan. Fashion parsing with weak color-category labels. IEEE Trans. Multimedia, 16(1):253--265, 2014.
[14]
S. Liu, J. Feng, Z. Song, T. Zhang, H. Lu, C. Xu, and S. Yan. Hi, magic closet, tell me what to wear! In Proc. ACM MM, 2012.
[15]
S. Liu, Z. Song, G. Liu, C. Xu, H. Lu, and S. Yan. Street-to-shop: Cross-scenario clothing retrieval via parts alignment and auxiliary set. In Proc. CVPR, 2012.
[16]
W. Liu, C. Mu, S. Kumar, and S.-F. Chang. Discrete graph hashing. In Proc. NIPS, 2014.
[17]
M. Norouzi, D. J. Fleet, and R. Salakhutdinov. Hamming distance metric learning. In Proc. NIPS, 2012.
[18]
M. Oquab, L. Bottou, I. Laptev, and J. Sivic. Learning and transferring mid-level image representations using convolutional neural networks. In Proc. CVPR, 2014.
[19]
P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun. Overfeat: Integrated recognition, localization and detection using convolutional networks. In Proc. ICLR, 2014.

Cited By

View all
  • (2024)Toward Fashion Intelligence in the Big Data Era: State-of-the-Art and Future ProspectsIEEE Transactions on Consumer Electronics10.1109/TCE.2023.328588070:1(36-57)Online publication date: Feb-2024
  • (2024)BangleFIR: bridging the gap in fashion image retrieval with a novel dataset of banglesMultimedia Tools and Applications10.1007/s11042-024-19698-4Online publication date: 10-Jul-2024
  • (2023)A Survey on Fashion Image RetrievalACM Computing Surveys10.1145/363655256:6(1-25)Online publication date: 13-Dec-2023
  • Show More Cited By

Index Terms

  1. Rapid Clothing Retrieval via Deep Learning of Binary Codes and Hierarchical Search

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    ICMR '15: Proceedings of the 5th ACM on International Conference on Multimedia Retrieval
    June 2015
    700 pages
    ISBN:9781450332743
    DOI:10.1145/2671188
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Sponsors

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 22 June 2015

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. convolutional neural network
    2. deep learning
    3. image retrieval

    Qualifiers

    • Short-paper

    Conference

    ICMR '15
    Sponsor:

    Acceptance Rates

    ICMR '15 Paper Acceptance Rate 48 of 127 submissions, 38%;
    Overall Acceptance Rate 254 of 830 submissions, 31%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)14
    • Downloads (Last 6 weeks)2
    Reflects downloads up to 01 Jan 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Toward Fashion Intelligence in the Big Data Era: State-of-the-Art and Future ProspectsIEEE Transactions on Consumer Electronics10.1109/TCE.2023.328588070:1(36-57)Online publication date: Feb-2024
    • (2024)BangleFIR: bridging the gap in fashion image retrieval with a novel dataset of banglesMultimedia Tools and Applications10.1007/s11042-024-19698-4Online publication date: 10-Jul-2024
    • (2023)A Survey on Fashion Image RetrievalACM Computing Surveys10.1145/363655256:6(1-25)Online publication date: 13-Dec-2023
    • (2023)Automatic recognition and classification of microalgae using an inception-v3 convolution neural network modelInternational Journal of Environmental Science and Technology10.1007/s13762-023-05209-921:4(4625-4634)Online publication date: 22-Sep-2023
    • (2023)Ornament image retrieval using few-shot learningInternational Journal of Multimedia Information Retrieval10.1007/s13735-023-00299-012:2Online publication date: 31-Aug-2023
    • (2022)Derin öğrenme temelli nesne tespiti algoritmaları kullanılarak kişiye özgü reklam sunulmasıPersonalized advertisement using deep learning-based object detection algorithmsBalıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi10.25092/baunfbed.87822424:1(10-28)Online publication date: 5-Jan-2022
    • (2022)Deep Learning System for Recycled Clothing Classification Linked to Cloud and Edge ComputingComputational Intelligence and Neuroscience10.1155/2022/68546262022Online publication date: 1-Jan-2022
    • (2022)A Decade Survey of Content Based Image Retrieval Using Deep LearningIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2021.308092032:5(2687-2704)Online publication date: May-2022
    • (2022)Clothing Flexible Retrieval Based on Attention Mechanism2022 5th International Conference on Data Science and Information Technology (DSIT)10.1109/DSIT55514.2022.9943979(1-7)Online publication date: 22-Jul-2022
    • (2022)Clothes Retrieval Using M-AlexNet With Mish Function and Feature Selection Using Joint Shannon’s Entropy Pearson’s Correlation CoefficientIEEE Access10.1109/ACCESS.2022.321832210(115469-115490)Online publication date: 2022
    • Show More Cited By

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media