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Improved Embeddings with Easy Positive Triplet Mining

This repository contains a PyTorch(1.5.0) implementation of Improved Embeddings with Easy Positive Triplet Mining(WACV2020)

Paper link: http://openaccess.thecvf.com/content_WACV_2020/papers/Xuan_Improved_Embeddings_with_Easy_Positive_Triplet_Mining_WACV_2020_paper.pdf

Update History: June 10, 2020 cleaned the code replace the learner object with directly train codes

Prepare the training data and testing data in python dictionary format.

For example:

data_dict = {'tra' : {'class_tra_01':[image path list],
                      'class_tra_02':[image path list],
                      'class_tra_03':[image path list],
                      ....,
                      'class_tra_XX':[image path list]}
                 
             'test': {'class_test_01':[image path list],
                      'class_test_02':[image path list],
                      'class_test_03':[image path list],
                      ....,
                      'class_test_XX':[image path list]}
            }

Replace Data and data_dict in the file main.py

We only have the color nomarlization info for CUB, CAR, SOP, In-shop cloth, and PKU vehicleID data. If you use other dataset please add the color nomarlization data in the file: _code/color_lib.py

We also supply our efficient recall@K accuracy calculation functions which are located in _code/Utils.py

This function is for CAR,CUB and SOP dataset
recall(Fvec, imgLab,rank=None) 
Fvec:   Feature vectors, N by D torch.Tensor
imgLab: Image label, python list
rank:   k of recall@k, python list

This function is for In-shop Cloth dataset
recall2(Fvec_val, Fvec_gal, imgLab_val, imgLab_gal,rank=None) 
Fvec_val:     Probe feature vectors, N_val by D torch.Tensor
Fvec_gal:     Gallary feature vectors, N_gal by D torch.Tensor
imgLab_val:   Probe image label, python list
imgLab_gal:   Gallary image label, python list
rank:         k of recall@k, python list

Please cite our paper, if you use these functions for recall calculation.

Requirements

Pytorch 1.5.0

Python 3.7

Updates

06/14/2020

Reorganize the training code.

Citation

@InProceedings{Xuan_2020_WACV,
author = {Xuan, Hong and Stylianou, Abby and Pless, Robert},
title = {Improved Embeddings with Easy Positive Triplet Mining},
booktitle = {The IEEE Winter Conference on Applications of Computer Vision (WACV)},
month = {March},
year = {2020}
}