cvpr2021kp2 / cvpr2021kp2

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Fast and Memory-Efficient Compact Bilinear Pooling

README

For a better user experience, we recommend you to directly use github repository github link

Prepare datasets

Dataset

CUB link

MIT link

DTD link

please unzip the downloaded datasets and then move them to data

Training

Step 1. Fine-tune the fc layer only.

CUDA_VISIBLE_DEVICES=0,1 python ./src/bilinear_cnn_fc_cub.py --base_lr 1 --batch_size 64 --epochs 81 --weight_decay 1e-6

Step 2. Fine-tune all layers.

CUDA_VISIBLE_DEVICES=0,1 python ./src/bilinear_cnn_all_cub.py --base_lr 1e-2 --batch_size 32 --epochs 50 --weight_decay 1e-3 --model "vgg_16_epoch_81.pth"

Run Script

You can also run the above three experiments by one script in background:

CUB:
nohup bash script_cub.sh &

MIT:
nohup bash script_mit.sh &

DTD:
nohup bash script_dtd.sh &

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