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# Re-ranking Person Re-identification with k-reciprocal Encoding # Re-ranking Person Re-identification with k-reciprocal Encoding
================================================================ ================================================================
@ -69,7 +68,7 @@ The new training/testing protocol split for CUHK03 in our paper is in the "evalu
matlab CUHK03_extract_feature.m matlab CUHK03_extract_feature.m
``` ```
3. Evaluation with our re-ranking method 3. Evaluation
```Shell ```Shell
# evaluation for Market-1501 # evaluation for Market-1501
matlab Market_1501_evaluation.m matlab Market_1501_evaluation.m
@ -85,7 +84,7 @@ You can download our pre-trained IDE models and IDE features, and put them in th
- IDE features [[Baiduyun]](https://pan.baidu.com/s/1c1TtKcw) [[Google drive]](https://drive.google.com/open?id=0B7TOZKXmIjU3ODhaRm8yN2QzRHc) - IDE features [[Baiduyun]](https://pan.baidu.com/s/1c1TtKcw) [[Google drive]](https://drive.google.com/open?id=0B7TOZKXmIjU3ODhaRm8yN2QzRHc)
Using the above IDE models and IDE features, you can reproduce the results with our re-ranking method as follows: Using the above IDE models and IDE features, you can reproduce the results as follows:
- Market-1501 - Market-1501
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# person-re-ranking # person-re-ranking
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