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Cross-modal Image-Graphics Retrieval by Neural Transfer Learning

Authors:

Fabian Junkert,

Markus Eberts,

Adrian Ulges,

Ulrich SchwaneckeAuthors Info & Claims

ICMR '17: Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval

Pages 330 - 337

https://doi.org/10.1145/3078971.3078994

Published: 06 June 2017 Publication History

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Cited By

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Wu FWang QWang ZYu SLi YZhang BLim E(2024)ITContrast: contrastive learning with hard negative synthesis for image-text matchingThe Visual Computer10.1007/s00371-024-03274-w40:12(8825-8838)Online publication date: 15-Feb-2024
https://doi.org/10.1007/s00371-024-03274-w
Liao SGavves ESnoek CAizawa KLew MSatoh S(2018)Searching and Matching Texture-free 3D Shapes in ImagesProceedings of the 2018 ACM on International Conference on Multimedia Retrieval10.1145/3206025.3206057(326-334)Online publication date: 5-Jun-2018
https://dl.acm.org/doi/10.1145/3206025.3206057

Index Terms

Cross-modal Image-Graphics Retrieval by Neural Transfer Learning
1. Computer systems organization
  1. Architectures
    1. Other architectures
      1. Neural networks
2. Computing methodologies
  1. Artificial intelligence
    1. Computer vision

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Information

Published In

ICMR '17: Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval

June 2017

524 pages

ISBN:9781450347013

DOI:10.1145/3078971

General Chairs:
Bogdan Ionescu
University Politehnica of Bucharest, Romania
,
Nicu Sebe
University of Trento, Italy
,
Program Chairs:
Jiashi Feng
National University of Singapore, Singapore
,
Martha Larson
Radboud University & Delft University of Technology, The Netherlands
,
Rainer Lienhart
University of Augsburg, Germany
,
Cees Snoek
University of Amsterdam & Qualcomm Research Netherlands, The Netherlands

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 the author(s) 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].

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Association for Computing Machinery

New York, NY, United States

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Published: 06 June 2017

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SIGMM

ICMR '17: International Conference on Multimedia Retrieval

June 6 - 9, 2017

Bucharest, Romania

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ICMR '17 Paper Acceptance Rate 33 of 95 submissions, 35%;

Overall Acceptance Rate 254 of 830 submissions, 31%

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Wu FWang QWang ZYu SLi YZhang BLim E(2024)ITContrast: contrastive learning with hard negative synthesis for image-text matchingThe Visual Computer10.1007/s00371-024-03274-w40:12(8825-8838)Online publication date: 15-Feb-2024
https://doi.org/10.1007/s00371-024-03274-w
Liao SGavves ESnoek CAizawa KLew MSatoh S(2018)Searching and Matching Texture-free 3D Shapes in ImagesProceedings of the 2018 ACM on International Conference on Multimedia Retrieval10.1145/3206025.3206057(326-334)Online publication date: 5-Jun-2018
https://dl.acm.org/doi/10.1145/3206025.3206057

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Deep representation-based transfer learning for deep neural networks

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