Skip to content
/ IMRAM Public
forked from HuiChen24/IMRAM

code for our CVPR2020 paper "IMRAM: Iterative Matching with Recurrent Attention Memory for Cross-Modal Image-Text Retrieval"

Notifications You must be signed in to change notification settings

gedaye11/IMRAM

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Requirements and Installation

We recommended the following dependencies.

import nltk
nltk.download()
> d punkt

Data preparation

Download the dataset files. We use splits produced by Andrej Karpathy. The raw images can be downloaded from from their original sources here, here and here.

The precomputed image features are extracted from the raw images using the bottom-up attention model from here. Image features for training set, validation set and testing set should be merged in order into one .npy file, respectively. More details about the image feature extraction can also be found in SCAN(https://github.com/kuanghuei/SCAN).

Data files can be found in SCAN (We use the same dataset split as theirs):

wget https://scanproject.blob.core.windows.net/scan-data/data_no_feature.zip

Place data_no_feature.zip in the directory of data.

Training and Evaluation

./script/tune_coco.sh

About

code for our CVPR2020 paper "IMRAM: Iterative Matching with Recurrent Attention Memory for Cross-Modal Image-Text Retrieval"

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 96.5%
  • Shell 3.5%