This is a pytorch re-implementation of Learning a Discriminative Filter Bank Within a CNN for Fine-Grained Recognition
This is a simple pytorch re-implementation of CVPR 2018 Learning a Discriminative Filter Bank Within a CNN for Fine-Grained Recognition.
This work still need to be updated. The features are summarized blow:
This work has been trained on 4 Titan V after epoch 120 with batchsize 56, Now I got best result Top1 85.140% Top5 96.237% which is lower than author's. You can download weights from weights. If use TenCrop transform in code, result can improve further.
Test Results:
wget http://www.vision.caltech.edu/visipedia-data/CUB-200-2011/CUB_200_2011.tgz
ln -s ./train path/to/code/dataset/train
ln -s ./test path/to/code/dataset/test
sh run.sh