Awesome
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}
}