Fetching the paper…
Reading the bibliography…
Fine-grained object categorization aims for distinguishing objects of subordinate categories that belong to the same entry-level object category.
M.-E. Nilsback and A. Zisserman, “Automated flower classification over a large number of classes,” in
2008
Earlier work this paper cites.
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei, “Imagenet: A large-scale hierarchical image database,” in
2009
Earlier work this paper cites.
P. Welinder, S. Branson, T. Mita, C. Wah, F. Schroff, S. Belongie, and P. Perona, “Caltech-UCSD Birds 200,” California Institute of Technology, Tech. Rep. CNS-TR-2010-001, 2010
2010
Earlier work this paper cites.
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie, “The caltech-ucsd birds-200-2011 dataset,” 2011
2011
Earlier work this paper cites.
A. Khosla, N. Jayadevaprakash, B. Yao, and F.-F. Li, “Novel dataset for fine-grained image categorization: Stanford dogs,” in
2011
Earlier work this paper cites.
O. M. Parkhi, A. Vedaldi, A. Zisserman, and C. V. Jawahar, “Cats and dogs,” in
2012
Earlier work this paper cites.
X. Wang, T. Zhang, D. R. Tretter, and Q. Lin, “Personal clothing retrieval on photo collections by color and attributes,”
2013
Earlier work this paper cites.
J. R. Uijlings, K. E. Van De Sande, T. Gevers, and A. W. Smeulders, “Selective search for object recognition,”
2013
Earlier work this paper cites.
N. Zhang, J. Donahue, R. Girshick, and T. Darrell, “Part-based r-cnns for fine-grained category detection,” in
2014
Earlier work this paper cites.
C. L. Zitnick and P. Dollár, “Edge boxes: Locating object proposals from edges,” in
2014
Earlier work this paper cites.
K. Simonyan and A. Zisserman, “Very deep convolutional networks for large-scale image recognition,”
2014
Earlier work this paper cites.
L. Xie, J. Wang, B. Zhang, and Q. Tian, “Fine-grained image search,”
2015
Earlier work this paper cites.
L. Zhu, J. Shen, H. Jin, L. Xie, and R. Zheng, “Landmark classification with hierarchical multi-modal exemplar feature,”
2015
Earlier work this paper cites.
M. Hadi Kiapour, X. Han, S. Lazebnik, A. C. Berg, and T. L. Berg, “Where to buy it: Matching street clothing photos in online shops,” in
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
T. Xiao, Y. Xu, K. Yang, J. Zhang, Y. Peng, and Z. Zhang, “The application of two-level attention models in deep convolutional neural network for fine-grained image classification,” in
2015
Earlier work this paper cites.
S. Ren, K. He, R. Girshick, and J. Sun, “Faster r-cnn: Towards real-time object detection with region proposal networks,” in
2015
Earlier work this paper cites.
R. Girshick, “Fast r-cnn,” in
2015
Earlier work this paper cites.
F. Yu and V. Koltun, “Multi-scale context aggregation by dilated convolutions,”
2015
Cited alongside, same era.
2015
Cited alongside, same era.
J. Krause, H. Jin, J. Yang, and L. Fei-Fei, “Fine-grained recognition without part annotations,” in
2015
Cited alongside, same era.
M. Simon and E. Rodner, “Neural activation constellations: Unsupervised part model discovery with convolutional networks,” in
2015
Cited alongside, same era.
T.-Y. Lin, A. RoyChowdhury, and S. Maji, “Bilinear cnn models for fine-grained visual recognition,” in
2015
Cited alongside, same era.
F. Zhou and Y. Lin, “Fine-grained image classification by exploring bipartite-graph labels,” in
2016
Later among the works it cites.
H. Yao, S. Zhang, Y. Zhang, J. Li, and Q. Tian, “Coarse-to-fine description for fine-grained visual categorization,”
2016
Later among the works it cites.
2016
Later among the works it cites.
S. Huang and D. Tao, “Real time fine-grained categorization with accuracy and interpretability,”
2016
Later among the works it cites.
B. Zhao, X. Wu, J. Feng, Q. Peng, and S. Yan, “Diversified visual attention networks for fine-grained object classification,”
2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
D. Yoo, S. Park, J.-Y. Lee, and I. So Kweon, “Multi-scale pyramid pooling for deep convolutional representation,” in
2015
Cited alongside, same era.
2015
Cited alongside, same era.
J. Johnson, A. Karpathy, and L. Fei-Fei, “Densecap: Fully convolutional localization networks for dense captioning,” in
2016
Cited alongside, same era.
L. Anne Hendricks, S. Venugopalan, M. Rohrbach, R. Mooney, K. Saenko, and T. Darrell, “Deep compositional captioning: Describing novel object categories without paired training data,” in
2016
Cited alongside, same era.
S. Huang, Z. Xu, D. Tao, and Y. Zhang, “Part-stacked cnn for fine-grained visual categorization,” in
2016
Cited alongside, same era.
H. Zhang, T. Xu, M. Elhoseiny, X. Huang, S. Zhang, A. Elgammal, and D. Metaxas, “Spda-cnn: Unifying semantic part detection and abstraction for fine-grained recognition,” in
2016
Cited alongside, same era.
C. Huang, Z. He, G. Cao, and W. Cao, “Task-driven progressive part localization for fine-grained object recognition,”
2016
Cited alongside, same era.
J. Fu, H. Zheng, and T. Mei, “Look closer to see better: Recurrent attention convolutional neural network for fine-grained image recognition,” in
2017
Later among the works it cites.
H. Zheng, J. Fu, T. Mei, and J. Luo, “Learning multi-attention convolutional neural network for fine-grained image recognition,” in
2017
Later among the works it cites.
X. Zhang, H. Xiong, W. Zhou, W. Lin, and Q. Tian, “Picking neural activations for fine-grained recognition,”
2017
Later among the works it cites.
Y. Guo, Y. Liu, S. Lao, E. M. Bakker, L. Bai, and M. S. Lew, “Bag of surrogate parts feature for visual recognition,”
2017
Later among the works it cites.
M. Lam, B. Mahasseni, and S. Todorovic, “Fine-grained recognition as hsnet search for informative image parts,” in
2017
Later among the works it cites.
2017
Later among the works it cites.
K. Jia, D. Tao, S. Gao, and X. Xu, “Improving training of deep neural networks via singular value bounding,” in
2017
Later among the works it cites.
C. Huang, H. Li, Y. Xie, Q. Wu, and B. Luo, “Pbc: polygon-based classifier for fine-grained categorization,”
2017
Later among the works it cites.
Z. Li, Y. Yang, X. Liu, S. Wen, and W. Xu, “Dynamic computational time for visual attention,”
2017
Later among the works it cites.
T. Berg, J. Liu, S. Woo Lee, M. L. Alexander, D. W. Jacobs, and P. N. Belhumeur, “Birdsnap: Large-scale fine-grained visual categorization of birds,” in
2018
Closest in time.
Y. Peng, X. He, and J. Zhao, “Object-part attention model for fine-grained image classification,”
2018
Closest in time.
X. Zhang, H. Xiong, W. Lin, and Q. Tian, “Weak to strong detector learning for simultaneous classification and localization,”
2018
Closest in time.
M. Jaderberg, K. Simonyan, A. Zisserman
2025
Closest in time.