2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDSMR-3.2
Paper Title Attention-based Multi-task Learning for Fine-grained Image Classification
Authors Dichao Liu, Nagoya University, Japan; Yu Wang, Ritsumeikan University, Japan; Kenji Mase, Nagoya University, Japan; Jien Kato, Ritsumeikan University, Japan
SessionSMR-3: Image and Video Representation
LocationArea F
Session Time:Tuesday, 21 September, 15:30 - 17:00
Presentation Time:Tuesday, 21 September, 15:30 - 17:00
Presentation Poster
Topic Image and Video Sensing, Modeling, and Representation: Image & video representation
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Abstract Fine-Grained Image Classification is an inherently challenging task because of its inter-class similarity and intra-class variance. Most existing studies solve this problem by localization-and-classification strategies, which, however, always causes the problem of information loss or heavy computational expenses. Instead of localization-and-classification strategy, we propose a novel end-to-end optimization procedure named Multi-Task Attention Learning (MTAL), which reinforces the neural network’ correspondence to attention regions. Experimental results on CUB-Birds and Stanford Cars show that our procedure distinctly outperforms the baselines and is comparable with state-of-the-art studies despite its simplicity.