Tao Zhang, XingYe Tian, Yikang Zhou, ShunPing Ji, Xuebo Wang, Xin Tao,
Yuan Zhang, Pengfei Wan, Zhongyuan Wang and Yu Wu
- DVIS and DVIS++ achieved 1st place in the VPS Track of the PVUW challenge at CVPR 2023.
2023.5.25 - DVIS and DVIS++ achieved 1st place in the VIS Track of the 5th LSVOS challenge at ICCV 2023.
2023.8.15
- DVIS++ is a universal video segmentation framework that supports VIS, VPS and VSS.
- DVIS++ can run in both online and offline modes.
- DVIS++ achieved SOTA performance on YTVIS 2019&2021&2022, OVIS, VIPSeg and VSPW datasets.
- OV-DVIS++ is the first open-vocabulary video universal segmentation framework with powerful zero-shot segmentation capability.
See Installation Instructions.
See Preparing Datasets for DVIS++.
See Getting Started with DVIS++.
Trained models are available for download in the DVIS++ Model Zoo.
@article{zhang2023dvis,
title={DVIS: Decoupled Video Instance Segmentation Framework},
author={Zhang, Tao and Tian, Xingye and Wu, Yu and Ji, Shunping and Wang, Xuebo and Zhang, Yuan and Wan, Pengfei},
journal={arXiv preprint arXiv:2306.03413},
year={2023}
}
@article{zhang2023dvisplus,
title={DVIS++: Improved Decoupled Framework for Universal Video Segmentation},
author={Tao Zhang and Xingye Tian and Yikang Zhou and Shunping Ji and Xuebo Wang and Xin Tao and Yuan Zhang and Pengfei Wan and Zhongyuan Wang and Yu Wu},
journal={arXiv preprint arXiv:2312.13305},
year={2023},
}This repo is largely based on Mask2Former, MinVIS, VITA, CTVIS, FC-CLIP and DVIS. Thanks for their excellent works.