This is the Matlab implements of our methods accepted in ACM MM 2017. [pdf]
This code implements
[1] Hervé Jégou and Andrew Zisserman. 2014. Triangulation embedding and democratic aggregation for image search. In CVPR.
[2] Thanh-Toan Do and Ngai-Man Cheung. 2017. Embedding based on function approximation for large scale image search. TPAMI (2017).
@INPROCEEDINGS{selectiveDeepConvFea,
author = {Tuan Hoang and Do, Thanh-Toan and Dang-Khoa Le Tan and Cheung, Ngai-Man},
title = {Selective Deep Convolutional Features for Image Retrieval},
bookTitle = {ACM Multimedia},
year = {2017},
month = {Oct},
}
The code include:
1) Modify the parameters in 'opt.m' file appropriately. 1) Run the following script
main
Filename | Description |
---|---|
README | This file |
main.m | The main script for running whole process |
opt.m | The script contains all parameter setting. |
extract_feature_map/ | Contains files for extracting conv. features. See the README file inside this folder for more information. |
tools/ | |
tools/make.m | Script to build the mex file for faemb and temb methods. |
tools/democratic/ | contains matlab script files for democratic pooling methods. |
tools/faemb/ | contains matlab script files for F-FAemb method. |
tools/faemb_mex/ | contains mex files for F-FAemb method. |
tools/triemb/ | contains matlab script/mex files for Triangular Embedding method. |
tools/evaluation/ | contains matlab script files for evaluation. |
tools/yael/ | contains the yael library |
utils | --- |
utils/embedding.m | Process embedding and aggregating |
utils/apply_mask.m | Compute and then apply mask on the conv. features. |
utils/crop_qim.m | Crop query images. |
utils/learn_rn.m | Learn projection (PCA/whitening) matrix |
utils/vecpostproc.m | Apply post-processing |
data/ | contains ground truth and data. In case you may want to retrain, please download the provided data and put them in this folder |
data/workdir/ | contains output files (i.e., parameters, embedded features) |