Affinity Relation-aware Fine-grained Bird Image Recognition for Robot Vision Tracking via Transformers

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

1 Scopus Citations
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Author(s)

  • Hai Liu
  • Cheng Zhang
  • Tingting Liu
  • Qingsong Xu

Detail(s)

Original languageEnglish
Title of host publication2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)
PublisherIEEE
Pages662-667
ISBN (electronic)978-1-6654-8109-0
ISBN (print)978-1-6654-8110-6
Publication statusPublished - Dec 2022

Conference

Title2022 IEEE International Conference on Robotics and Biomimetics (ROBIO 2022)
LocationChina Sheraton Grand Xishuangbanna Hotel
PlaceChina
CityJinghong
Period5 - 9 December 2022

Abstract

Fine-grained Bird Image Recognition dedicates to achieve accurate bird image classification and it is also a fundamental task in robot vision tracking. Given that endangered bird surveillance and conservation is of great significance for bird protection from extinction, automated approaches are in need to facilitate bird surveillance. In this work, we propose a novel robot vision tracking based method for bird surveillance with an affinity relation-aware model named TBNet that combines CNN and Transformer architecture and has a novel feature selection (FS) module. Specifically, CNN is employed to extract superficial information. Transformer is utilized for exploiting abstract semantic affinity relations. FS module is introduced to reveal discriminative features. Comprehensive experiments demonstrate that can achieve state-of-the-art performance on the CUB-200-2011 dataset (91.0%) and the NABirds dataset (90.9%). © 2022 IEEE

Citation Format(s)

Affinity Relation-aware Fine-grained Bird Image Recognition for Robot Vision Tracking via Transformers. / Liu, Hai; Zhang, Cheng; Xie, Bochen et al.
2022 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, 2022. p. 662-667.

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review