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@ -4,6 +4,11 @@ A pytorch implementation of the "Selective Convolutional Descriptor Aggregation"
## NOTE ## NOTE
cpu-only version cpu-only version
no in [1]
```
train_data_L31a(i,:) = train_data_L31a(i,:) ./ norm(train_data_L31a(i,:));
```
[largestConnectComponent](https://blog.csdn.net/xuyangcao123/article/details/81023732) [largestConnectComponent](https://blog.csdn.net/xuyangcao123/article/details/81023732)
@ -15,13 +20,13 @@ install requirements
pip install -r requirements.txt; pip install -r requirements.txt;
``` ```
On CUB and split dataset in 'CUB_200.py'. On CUB and split dataset in `CUB_200.py`.
random split CUB-200-2011 results: random split CUB-200-2011 results:
||top1|top5 ||top1|top5
---|:--:|---: ---|:--:|---:
CUB|-|- CUB|0.46|0.71
>Wei X S , Luo J H , Wu J , et al. Selective Convolutional Descriptor Aggregation for Fine-Grained Image Retrieval[J]. IEEE Transactions on Image Processing, 2017, 26(6):2868-2881. >[1] Wei X S , Luo J H , Wu J , et al. Selective Convolutional Descriptor Aggregation for Fine-Grained Image Retrieval[J]. IEEE Transactions on Image Processing, 2017, 26(6):2868-2881.