AGNN

Code for ICCV 2019 paper: Zero-shot Video Object Segmentation via Attentive Graph Neural Networks

Quick Start

Testing

1. Install pytorch (version:1.0.1).

2. Download the pretrained model, put in the snapshots folder. Run 'test_iteration_conf_gnn.py' and change the davis dataset path, pretrainde model path and result path.

3. Run command: python test_iteration_conf_gnn.py --dataset davis --gpus 0

4. Post CRF processing code: https://github.com/lucasb-eyer/pydensecrf

The pretrained weight can be download from GoogleDrive.

The segmentation results on DAVIS-2016, Youtube-objects and DAVIS-2017 datasets can be download from GoogleDiver.

Citation

If you find the code and dataset useful in your research, please consider citing:

@InProceedings{Wang_2019_ICCV,

author = {Wang, Wenguan and Lu, Xiankai and Shen, Jianbing and Crandall, David J. and Shao, Ling},

title = {Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks},

booktitle = {The IEEE International Conference on Computer Vision (ICCV)},

year = {2019} }

Other related projects/papers:

See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks(CVPR19)

Saliency-Aware Geodesic Video Object Segmentation (CVPR15)

Learning Unsupervised Video Primary Object Segmentation through Visual Attention (CVPR19)

Any comments, please email: [email protected]