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chenjoya / crossgcn

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README

Cross Graph Align (CrossGCN)

Acknowledgements

This repository is supported by 2018YFB1004300.

Chen J, Du H, Wu Y F, et al. Cross-modal video moment retrieval based on visual-textual relationship alignment (in
Chinese). Sci Sin Inform, 2020, 50: 862–876, doi: 10.1360/SSI-2019-0292

Requirements:

  • CUDA >= 9.0

Installation

# create and activate a clean conda env
conda create -n crossgcn
conda activate crossgcn 

# install the right pip and dependencies for the fresh python
conda install ipython pip

# install some dependencies
pip install yacs h5py terminaltables tqdm
# Note: you can use tsinghua mirror to speed up downloading if you are in China
# pip install yacs h5py terminaltables tqdm -i https://pypi.tuna.tsinghua.edu.cn/simple

# follow PyTorch installation in https://pytorch.org/get-started/locally/
# we give the instructions for CUDA 10.1, others are also okay
conda install pytorch torchvision cudatoolkit=10.1 torchtext -c pytorch
# Note: you can use tsinghua mirror to speed up downloading if you are in China
# conda install pytorch torchvision cudatoolkit=10.1 torchtext -c https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/

# clone crossgcn and enjoy it!
git clone https://github.com/ChenJoya/crossgcn

Results

1. TACoS Dataset

Repo Rank1@0.1 Rank1@0.3 Rank1@0.5 Rank5@0.1 Rank5@0.3 Rank5@0.5
CrossGCN 51.9 39.8 26.4 74.5 60.0 47.2

2. ActivityNet Dataset

Repo Rank1@0.3 Rank1@0.5 Rank1@0.7 Rank5@0.3 Rank5@0.5 Rank5@0.7
CrossGCN 62.7 47.2 27.9 88.1 79.1 64.2

Dataset

Please refer to DATASET.md to prepare datasets.

Quick Start

We provide scripts for simplifying training and inference. Please refer to scripts/train.sh, scripts/eval.sh.

Support

Please open a new issue. We would like to answer it. Please feel free to contact me: chenjoya@foxmail.com if you need my help.

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