Unified-Lift

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Code Release for CVPR 2025, "Rethinking End-to-End 2D to 3D Scene Segmentation in Gaussian Splatting"

Unified-Lift 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

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# Unified-Lift (CVPR 2025)
## [[Paper](https://github.com/Runsong123/Unified-Lift/blob/main/material/Unified_Lift.pdf)]

> **Runsong Zhu**, Shi Qiu, Zhengzhe Liu, Ka-Hei Hui, Qianyi Wu, Pheng-Ann Heng, Chi-Wing Fu
>

>**TL;DR**: Our paper presents a new and effective end-to-end lifting framework that achieves state-of-the-art (SOTA) performance for 3D Gaussian segmentation, without the need for pre-processing (e.g., video tracking) or post-processing (e.g., clustering).

### Comparisons with existing works

![image](https://github.com/Runsong123/Unified-Lift/blob/main/material/Teaser.png)

### 3D point-level visualization
![image](https://github.com/Runsong123/Unified-Lift/blob/main/material/3D_Segmentation.png)

### How to use the code. 
To use Unified-Lift, please refer to the [Usage](doc/Usage.md) guide. (currently under construction).

# Citation
If you find this work useful in your research, please cite our paper:
```
@article{zhu2025rethinking,
  title={Rethinking End-to-End 2D to 3D Scene Segmentation in Gaussian Splatting},
  author={Zhu, Runsong and Qiu, Shi and Liu, Zhengzhe and Hui, Ka-Hei and Wu, Qianyi and Heng, Pheng-Ann and Fu, Chi-Wing},
  journal={arXiv preprint arXiv:2503.14029},
  year={2025}
}

```

## Thanks
This code is based on [Gaussian Grouping](https://github.com/lkeab/gaussian-grouping), [OmniSeg3D-GS](https://github.com/OceanYing/OmniSeg3D-GS), [Panoptic-Lifting](https://github.com/nihalsid/panoptic-lifting). We thank the authors for releasing their code.

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