Benchmark for Image Retrieval (BKIR)

This project tries to build a benchmark for image retrieval, particularly for Instance-level image retrieval.

Running on Scores Dataset

Fisher vector and VLAD are both currently working on the scores dataset. To run them,

1. install score-retrieval,
2. run make, follow the instructions, then run make again,
3. run make yael,
4. run make hesaff,
5. run make setup-dataset,
6. run the commands in the fv or vlad make target manually (make fv/make vlad isn't working right now for some reason).

Note: The training parameters in gmm.py (for FV) and kmeans.py (for VLAD) have been massively reduced for ease of testing. If you want a real training run, increase them.

Methods

method	feature	mAP (best)	status	links
fc_retrieval	CNN	60.2%	finished	fc_retrieval
rmac_retrieval	CNN	to be tested	finished	rmac_retrieval
crow_retrieval	CNN	to be tested	finished	crow_retrieval
fv_retrieval	SIFT	67.29%	finished	fv_retrieval
vlad_retrieval	SIFT	63.13%	finished	vlad_retrieval

the methods on above have the following characteristics:

• Low dimension
• Time - tested
• Used in industry

Contribution

If you are interested in this project, feel free to contribute your code. Only Python and C++ code are accepted.