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Towards Fine-Grained Recognition: Joint Learning for Object Detection and Fine-Grained Classification

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Advances in Visual Computing (ISVC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11845))

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Abstract

Fine-grained classification is a challenging problem due to subtle differences between intra-class categories. In practice, fine-grained classification is often used in conjunction with object detection algorithms to locate and identify object categories. Despite recent achievements in both fine-grained classification and object detection, few works have demonstrated datasets or solutions to simultaneously handle both tasks. We make two contributions to this problem. Firstly, we construct a fine-grained classification and detection benchmark. Secondly, we show an end-to-end convolutional neural networks (CNNs) architecture to detect and classify fine-grained objects. Experimental results verify that our networks perform favorably against alternatives.

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Authors and Affiliations

  1. Department of Computer and Information Sciences, University of Delaware, Newark, DE, USA

    Qiaosong Wang & Christopher Rasmussen

Authors
  1. Qiaosong Wang
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  2. Christopher Rasmussen
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Corresponding author

Correspondence to Qiaosong Wang .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, NV, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. University of Nevada, Reno, NV, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Daniela Ushizima

  6. Latent AI, Palo Alto, CA, USA

    Sek Chai

  7. Texas A&M University, College Station, TX, USA

    Shinjiro Sueda

  8. Louisiana State University, Baton Rouge, LA, USA

    Xin Lin

  9. University of North Carolina at Charlotte, Charlotte, NC, USA

    Aidong Lu

  10. École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Daniel Thalmann

  11. Notre Dame University, Notre Dame, IN, USA

    Chaoli Wang

  12. Bosch Research North America, Palo Alto, CA, USA

    Panpan Xu

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Wang, Q., Rasmussen, C. (2019). Towards Fine-Grained Recognition: Joint Learning for Object Detection and Fine-Grained Classification. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2019. Lecture Notes in Computer Science(), vol 11845. Springer, Cham. https://doi.org/10.1007/978-3-030-33723-0_27

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  • DOI: https://doi.org/10.1007/978-3-030-33723-0_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33722-3

  • Online ISBN: 978-3-030-33723-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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