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Fully Convolutional Attention Networks for Fine-Grained Recognition

Fine-grained recognition is challenging due to its subtle local inter-class differences versus large intra-class variations such as poses. A key to address this problem is to localize discriminative parts to extract pose-invariant features.

Data and Resources

Cite this as

Xiao Liu, Tian Xia, Jiang Wang, Yi Yang, Feng Zhou, Yuanqing Lin (2024). Dataset: Fully Convolutional Attention Networks for Fine-Grained Recognition. https://doi.org/10.57702/jovhuqnn

DOI retrieved: December 16, 2024

Additional Info

Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.1603.06765
Author Xiao Liu
More Authors
Tian Xia
Jiang Wang
Yi Yang
Feng Zhou
Yuanqing Lin
Homepage https://arxiv.org/abs/1704.07735