Ylexx / Hierarchical-Bilinear-Pooling_Resnet_Pytorch

A pytorch reimplementation of Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition in Resnet.

Hierarchical-Bilinear-Pooling_Resnet_Pytorch

A reimplementation of Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition in Resnet.

Requirements

• python 2.7
• pytorch 0.4.1

Train

Step 1.

• Download the resnet pre-training parameters.

• Download the CUB-200-2011 dataset. CUB-download

Step 2.

• Set the path to the dataset and resnet parameters in the code.

Step 3. Train the fc layer only.

• python train_firststep.py

Step 4. Fine-tune all layers. It gets an accuracy of around 86% on CUB-200-2011 when using resnet-50.

• python train_finetune.py

If you are interested in this code, you can continue to adjust the model structure, and try more resnet models, you should get better results.

Official Caffe implementation of Hierarchical Bilinear Pooling for Fine-Grained Visual Recognition is HERE