VLGrammar: Grounded Grammar Induction of Vision and Language

Overview

Data

Data can be downloaded here

SetUp

conda create -n vlgrammar python=3.7 pytorch=1.7.1 torchvision -c pytorch
conda activate vlgrammar

pip install -r requirements.txt

git clone --branch infer_pos_tag https://github.com/zhaoyanpeng/pytorch-struct.git
cd pytorch-struct
pip install -e 

Clustering

cd SCAN
python simclr.py --config_env configs/env.yml --config_exp configs/pretext/simclr_partit_chair.yml
python scan.py --config_env configs/env.yml --config_exp configs/scan/scan_partit_chair.yml

or use our pretrained model

Grammar Induction

cd VLGrammr
python train.py or python train.py --type chair

Checkpoints

Model checkpoints can be downloaded here

Citation

@misc{hong2021vlgrammar,
      title={VLGrammar: Grounded Grammar Induction of Vision and Language}, 
      author={Yining Hong and Qing Li and Song-Chun Zhu and Siyuan Huang},
      year={2021},
      journal={ICCV},
}

paper

Acknowledgements

Parts of the codes are based on vpcfg and SCAN

Owner
Yining Hong
https://evelinehong.github.io
Yining Hong
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