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Advances in Computer Vision and Pattern Recognition

Visual Attributes

Editors: Feris, Rogerio Schmidt, Lampert, Christoph, Parikh, Devi (Eds.)

  • The first book to introduce the topic of visual attributes, and cover emerging concepts such as zero-shot learning
  • Covers theoretical aspects of visual attribute learning, as well as practical computer vision applications
  • Includes contributions from world-renowned scientists in machine learning and computer vision, and at the intersection with computational linguistics and human-machine interaction
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Buy this book

eBook $109.00
price for USA (gross)
  • ISBN 978-3-319-50077-5
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $139.00
price for USA
  • ISBN 978-3-319-50075-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

This unique text/reference provides a detailed overview of the latest advances in machine learning and computer vision related to visual attributes, highlighting how this emerging field intersects with other disciplines, such as computational linguistics and human-machine interaction. Topics and features: presents attribute-based methods for zero-shot classification, learning using privileged information, and methods for multi-task attribute learning; describes the concept of relative attributes, and examines the effectiveness of modeling relative attributes in image search applications; reviews state-of-the-art methods for estimation of human attributes, and describes their use in a range of different applications; discusses attempts to build a vocabulary of visual attributes; explores the connections between visual attributes and natural language; provides contributions from an international selection of world-renowned scientists, covering both theoretical aspects and practical applications.

About the authors

Dr. Rogerio Schmidt Feris is a manager at IBM T.J. Watson Research Center, New York, USA, where he leads research in computer vision and machine learning.

Dr. Christoph H. Lampert is a professor at the Institute of Science and Technology Austria, where he serves as the Principal Investigator of the Computer Vision and Machine Learning Group.

Dr. Devi Parikh is an assistant professor in the School of Interactive Computing at Georgia Tech, USA, where she leads the Computer Vision Lab.

Table of contents (13 chapters)

  • Introduction to Visual Attributes

    Feris, Rogerio Schmidt (et al.)

    Pages 1-7

  • An Embarrassingly Simple Approach to Zero-Shot Learning

    Romera-Paredes, Bernardino (et al.)

    Pages 11-30

  • In the Era of Deep Convolutional Features: Are Attributes Still Useful Privileged Data?

    Sharmanska, Viktoriia (et al.)

    Pages 31-48

  • Divide, Share, and Conquer: Multi-task Attribute Learning with Selective Sharing

    Chen, Chao-Yeh (et al.)

    Pages 49-85

  • Attributes for Image Retrieval

    Kovashka, Adriana (et al.)

    Pages 89-117

Buy this book

eBook $109.00
price for USA (gross)
  • ISBN 978-3-319-50077-5
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $139.00
price for USA
  • ISBN 978-3-319-50075-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Visual Attributes
Editors
  • Rogerio Schmidt Feris
  • Christoph Lampert
  • Devi Parikh
Series Title
Advances in Computer Vision and Pattern Recognition
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG
eBook ISBN
978-3-319-50077-5
DOI
10.1007/978-3-319-50077-5
Hardcover ISBN
978-3-319-50075-1
Series ISSN
2191-6586
Edition Number
1
Number of Pages
VIII, 364
Number of Illustrations and Tables
5 b/w illustrations, 137 illustrations in colour
Topics