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The devil is in the details: an evaluation of recent feature encoding methods
K. Chatfield, V. Lempitsky, A. Vedaldi, and A. Zisserman · 2011
Earlier work this paper cites.
Novel dataset for fine-grained image categorization
Aditya Khosla, Nityananda Jayadevaprakash, Bangpeng Yao, and Li Fei-Fei · 2011
Earlier work this paper cites.

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The caltech-ucsd birds-200-2011 dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
Cited alongside, same era.
Dog breed classification using part localization
J. Liu, A. Kanazawa, D. Jacobs, and P. Belhumeur · 2012
Cited alongside, same era.

Then

Cats vs dogs
O. Parkhi, A. Vedaldi, C. V. Jawahar, and A. Zisserman · 2012
Later among the works it cites.

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2013

Fine-Grained Visual Classification of Aircraft

Maji, Subhransu, Rahtu, Esa, Kannala, Juho et al.

Understand

This paper introduces FGVC-Aircraft, a new dataset containing 10,000 images of aircraft spanning 100 aircraft models, organised in a three-level hierarchy.

At the finer level, differences between models are often subtle but always visually measurable, making visual recognition challenging but possible.
A benchmark is obtained by defining corresponding classification tasks and evaluation protocols, and baseline results are presented.
The construction of this dataset was made possible by the work of aircraft enthusiasts, a strategy that can extend to the study of number of other object classes.