Pytorch models definition and test for image retrieval
This is the implementation of the paper :
Portaz, M., Kohl, M., Chevallet, J. P., Quénot, G., & Mulhem, P. (2019). Object instance identification with fully convolutional networks. Multimedia Tools and Applications, 78(3), 2747-2764.
If you use it, please cite :
@article{portaz2019object,
title={Object instance identification with fully convolutional networks},
author={Portaz, Maxime and Kohl, Matthias and Chevallet, Jean-Pierre and Qu{\'e}not, Georges and Mulhem, Philippe},
journal={Multimedia Tools and Applications},
volume={78},
number={3},
pages={2747--2764},
year={2019},
publisher={Springer}
}
Test several approaches for images retrieval:
* Feature Extraction from Pretrained CNN
* Pretrained CNN finetuning
* Siamese network from scratch
* Siamese network with pretrained network
TrainClassif
Finetune a CNN for classification over few examples
Finetune only the classifier or the entire network
TrainSiamese
Train a siamese network with pairs selection for image retrieval