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https://github.com/nvlabs/minvis
https://github.com/nvlabs/minvis
Last synced: 3 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/nvlabs/minvis
- Owner: NVlabs
- License: other
- Created: 2022-07-28T04:37:23.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2022-09-16T18:03:25.000Z (about 2 years ago)
- Last Synced: 2024-06-24T05:55:12.698Z (5 months ago)
- Language: Python
- Size: 149 KB
- Stars: 262
- Watchers: 5
- Forks: 23
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- StarryDivineSky - NVlabs/MinVIS
README
# MinVIS: A Minimal Video Instance Segmentation Framework without Video-based Training
[De-An Huang](https://ai.stanford.edu/~dahuang/), [Zhiding Yu](https://chrisding.github.io/), [Anima Anandkumar](http://tensorlab.cms.caltech.edu/users/anima/)
[[`arXiv`](https://arxiv.org/abs/2208.02245)] [[`Project`]()] [[`BibTeX`](#CitingMinVIS)]
### Features
* Video instance segmentation by only training an image instance segmentation model.
* Support major video instance segmentation datasets: YouTubeVIS 2019/2021, Occluded VIS (OVIS).### Qualitative Results on Occluded VIS
## Installation
See [installation instructions](INSTALL.md).
## Getting Started
See [Preparing Datasets for MinVIS](datasets/README.md).
See [Getting Started with MinVIS](GETTING_STARTED.md).
## Model Zoo
Trained models are available for download in the [MinVIS Model Zoo](MODEL_ZOO.md).
## License
The majority of MinVIS is made available under the [Nvidia Source Code License-NC](LICENSE). The trained models in the [MinVIS Model Zoo](MODEL_ZOO.md) are made available under the [CC BY-NC-SA 4.0 License](https://creativecommons.org/licenses/by-nc-sa/4.0/).
Portions of the project are available under separate license terms: Mask2Former is licensed under a [MIT License](https://github.com/facebookresearch/Mask2Former/blob/main/LICENSE). Swin-Transformer-Semantic-Segmentation is licensed under the [MIT License](https://github.com/SwinTransformer/Swin-Transformer-Semantic-Segmentation/blob/main/LICENSE), Deformable-DETR is licensed under the [Apache-2.0 License](https://github.com/fundamentalvision/Deformable-DETR/blob/main/LICENSE).
```BibTeX
@inproceedings{huang2022minvis,
title={MinVIS: A Minimal Video Instance Segmentation Framework without Video-based Training},
author={De-An Huang and Zhiding Yu and Anima Anandkumar},
journal={NeurIPS},
year={2022}
}
```## Acknowledgement
This repo is largely based on Mask2Former (https://github.com/facebookresearch/Mask2Former).