HOI Transformer

Code for CVPR 2021 accepted paper End-to-End Human Object Interaction Detection with HOI Transformer.

Reproduction

We recomend you to setup in the following steps:

1.Clone the repo.

git clone https://github.com/bbepoch/HoiTransformer.git

2.Download the MS-COCO pretrained DETR model.

cd data/detr_coco && bash download_model.sh

3.You are supposed to make a soft link named 'images' in 'data/hico/' to refer to your HICO-DET path, or your will have to modify the data path manually in hico.py.

ln -s /path-to-your-hico-det-dataset/hico_20160224_det/images images

4.Train a model.

python3 -m torch.distributed.launch --nproc_per_node=8 --use_env main.py --epochs=250 --lr_drop=200 --dataset_file=hico --batch_size=2 --backbone=resnet50

5.Prepare evaluation tool.

cd data/hico && unzip eval.zip

6.Test a model.

python3 test.py --dataset_file=hico --batch_size=1 --log_dir=./ --backbone=resnet50 --model_path=your_model_path

Citation

@inproceedings{zou2021_hoitrans,
  author = {Zou, Cheng and Wang, Bohan and Hu, Yue and Liu, Junqi and Wu, Qian and Zhao, Yu and Li, Boxun and Zhang, Chenguang and Zhang, Chi and Wei, Yichen and Sun, Jian},
  title = {End-to-End Human Object Interaction Detection with HOI Transformer},
  booktitle={CVPR},
  year = {2021},
}

Acknowledgement

We sincerely thank all previous works, especially DETR, PPDM, iCAN, for some of the codes are built upon them.

sx14/HoiTransformer

HOI Transformer

Reproduction

Citation

Acknowledgement