Fine-Grained-Image-Retrieval

Something for myself

https://arxiv.org/abs/1605.05395

https://arxiv.org/abs/1604.04994

https://arxiv.org/abs/1607.07614

[1]      Zhang, X., Xiong, H., Zhou, W., Lin, W., & Tian, Q. Picking Deep Filter Responses for Fine-Grained Image Recognition.

[2]      Zhang, H., Xu, T., Elhoseiny, M., Huang, X., Zhang, S., Elgammal, A., & Metaxas, D. SPDA-CNN: Unifying Semantic Part Detection and Abstraction for Fine-grained Recognition.

[3]      Huang, S., Xu, Z., Tao, D., & Zhang, Y. Part-Stacked CNN for Fine-Grained Visual Categorization.

[4]      Wang, Y., Choi, J., Morariu, V. I., & Davis, L. S. Mining Discriminative Triplets of Patches for Fine-Grained Classification.

[5]      Zhou, Feng, & Yuanqing Lin. Fine-grained Image Classification by Exploring Bipartite-Graph Labels.

[6]      Zhang, X., Zhou, F., Lin, Y., & Zhang, S. Embedding Label Structures for Fine-Grained Feature Representation.

[7]      Cui, Y., Zhou, F., Lin, Y., & Belongie, S. Fine-grained categorization and dataset bootstrapping using deep metric learning with humans in the loop.