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Benchmark for Image Retrieval (BKIR)

License

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

Methods

The following methods are evaluated on Oxford Building dataset. The evaluation adopts mean Average Precision (mAP), which is computed using the code provided by compute_ap.cpp.

method feature mAP (best) status evalute code
fc_retrieval CNN 60.2% finished fc_retrieval
rmac_retrieval RMAC 75.7%(256d, crop, qe) finished rmac_retrieval
crow_retrieval CROW 72.8%(256d, crop, qe) finished crow_retrieval
fv_retrieval SIFT 67.29% finished fv_retrieval
vlad_retrieval SIFT 63.13% finished vlad_retrieval
fv_retrieval SOSNet 50.73% ongoing -
vlad_retrieval SOSNet - ongoing -

the methods on above have the following characteristics:

  • Low dimension
  • Time - tested, and are dimanstracted effectively
  • Used in industry

Contribution

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

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CNN CBIR benchmark (ongoing)

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