GitHub - Atmegal/Comprehensive-Distance-Preserving-Autoencoders-for-Cross-Modal-Retrieval: The code of Comprehensive Distance-Preserving Autoencoders for Cross-Modal Retrieval

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
Auto1.py		Auto1.py
Knn.py		Knn.py
README.txt		README.txt
decoder.py		decoder.py

Repository files navigation

This is the source code of our ACM Multimedia Conference 2018 paper "Comprehensive Distance-Preserving Autoencoders for Cross-Modal Retrieval", Please cite the following paper if you use our code.

Yibing Zhan,Jun Yu,Zhou Yu,Rong Zhang,Dacheng Tao,Qi Tian,"Comprehensive Distance-Preserving Autoencoders for Cross-Modal Retrieval", ACM MM 2018


Usage
For Wikipedia-Multiple dataset:

1.Generate the Comprehensive Distance-Preserving Autoencoders by using the code:Auto1.py
2. Get the best data after training by using the code:decoder.py
3. Unsupervised Cross-Modal Similarity Measurement is used to further improve the retrieval performance by using the code:Knn.py


For more information, please refer to our ACM MM paper.