zjnhq/swiftnet

implement of SwiftNet:Real-time Video Object Segmentation

SwiftNet

The official PyTorch implementation of SwiftNet:Real-time Video Object Segmentation, which has been accepted by CVPR2021.

Requirements

• Python >= 3.6
• Pytorch 1.5
• Numpy
• Pillow
• opencv-python
• scipy
• tqdm

Training

• The training pipeline of Swiftnet is similar with the training pipeline of STM, which can be found in our reproduced STM training code.

Inference

Usage

python eval.py -g 0 -y 17 -s val -D 'path to davis'

Performance

Performance on Davis-17 val set.

backbone	J&F	J	F	FPS	weights
resnet-18	77.6	75.5	79.7	65	link

Note: The FPS is tested on one P100, which does not include the time of image loading and evaluation cost.

Acknowledgement

This repository is partially founded on the official STM repository.

Citation

If you find this repository helpful and want to cite SwiftNet in your own projects, please use the following citation info.

@inproceedings{wang2021swiftnet,
  title={SwiftNet: Real-time Video Object Segmentation},
  author={Wang, Haochen and Jiang, Xiaolong and Ren, Haibing and Hu, Yao and Bai, Song},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={1296--1305},
  year={2021}
}