---
pipeline_tag: robotics
tags:
- RGB-D SLAM
- dense-reconstruction
- camera-tracking
---

# PROFusion: Robust and Accurate Dense Reconstruction via Camera Pose Regression and Optimization

[ICRA 2026] PROFusion is a simple yet effective system for real-time camera tracking and dense scene reconstruction, providing both robustness against unstable camera motions and accurate reconstruction results.

This repository contains pre-trained weights for the **pose regression module**, which estimates the relative camera pose (in metric-scale) between two RGB-D frames.

- **Paper:** [PROFusion: Robust and Accurate Dense Reconstruction via Camera Pose Regression and Optimization](https://arxiv.org/abs/2509.24236)
- **Code:** [GitHub Repository](https://github.com/siyandong/PROFusion)

## Method Overview

Real-time dense scene reconstruction during unstable camera motions is crucial for robotics, yet current RGB-D SLAM systems often fail when cameras experience large viewpoint changes, fast motions, or sudden shaking. PROFusion addresses this challenge through a combination of learning-based initialization with optimization-based refinement. 

The system employs a camera pose regression network to predict metric-aware relative poses from consecutive RGB-D frames, which serve as reliable starting points for a randomized optimization algorithm that further aligns depth images with the scene geometry. The system operates in real-time, showcasing that combining simple and principled techniques can achieve both robustness for unstable motions and accuracy for dense reconstruction.

## Citation

If you find this work helpful in your research, please consider citing: 

```bibtex
@article{dong2025profusion,
  title={PROFusion: Robust and Accurate Dense Reconstruction via Camera Pose Regression and Optimization},
  author={Dong, Siyan and Wang, Zijun and Cai, Lulu and Ma, Yi and Yang, Yanchao},
  journal={arXiv preprint arXiv:2509.24236},
  year={2025}
}
```

## Acknowledgments

The implementation is based on several inspiring works in the community, including [DUSt3R](https://github.com/naver/dust3r), [SLAM3R](https://github.com/PKU-VCL-3DV/SLAM3R), [Reloc3r](https://github.com/ffrivera0/reloc3r), and [ROSEFusion](https://github.com/jzhzhang/ROSEFusion).