S3Net

Introduction

PyTorch code for the ICME 2021 paper Selective, Structural, Subtle: Trilinear Spatial-Awareness for Few-Shot Fine-Grained Visual Recognition.

Dependencies

• conda env create -f pytorch.yml

Training

• For example: Standford Cars dataset (1-shot)
• python mytrain_cars.py --nExemplars 1 --gpu-devices 0

Testing

• For example: Standford Cars dataset (1-shot)

• python test_car.py --nExemplars 1 --gpu-devices 0 --resume ./result/car/5-shot-seed1-conv4_myspp_globalcos_few_loss/best_model.pth.tar

Citation

@inproceedings{wu2021selective, 
title={Selective, Structural, Subtle: Trilinear Spatial-Awareness for Few-Shot Fine-Grained Visual Recognition}, 
author={Wu, Heng and Zhao, Yifan and Li, Jia}, 
booktitle={2021 IEEE International Conference on Multimedia and Expo (ICME)},
pages={1--6}, year={2021}, organization={IEEE} 
}