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language:
- en
tags:
- arxiv:2609.15795
- pytorch
- computer-vision
- 3d-reconstruction
- uncertainty-estimation
- streaming
datasets:
- tartanair
base_model: robbyant/lingbot-map
---
# SURE-Map: Self-Correcting Streaming Geometric Foundation Models
**Mingkai Liu, Hao Zhao, Xingxing Zuo**
[Paper](https://arxiv.org/abs/2609.15795) 路 [Code](https://github.com/RCL-Robotics/SURE-map) 路 [Project page](https://mingkai-liu.github.io/projects/sure-map/) 路 [Video](https://www.youtube.com/watch?v=vIKJFzLCtMc)
SURE-Map equips streaming geometric foundation models with cross-view geometric uncertainty and multi-timescale self-correction. Cross-view uncertainty assesses the geometric consistency of jointly predicted pose and depth, supporting dense-point filtering and local translation optimization. Sparse keyframe-window inference provides longer-range geometric evidence for scale recalibration.
## Checkpoint
`uncertainty.pt` is the trained **cross-view geometric uncertainty head** checkpoint used in the reported experiments. It is used together with the SURE-Map implementation and a separately downloaded LingBot-Map backbone; it is not a standalone reconstruction model.
The checkpoint is copied without modification from the official [SURE-Map repository](https://github.com/RCL-Robotics/SURE-map/tree/main/checkpoints).
- File size: 199,159,826 bytes.
- SHA-256: `a1b8cdd76ae33768e738554cece65b0113770e48824064c7a92b59752b06e1a7`.
- Training data: TartanAir v1; the backbone is frozen during uncertainty-head training.
## Download and use
Clone the code and follow its [environment setup instructions](https://github.com/RCL-Robotics/SURE-map#environment-setup):
```bash
git clone https://github.com/RCL-Robotics/SURE-map.git SURE-Map
cd SURE-Map
mkdir -p checkpoints
```
Download the uncertainty checkpoint into `checkpoints/uncertainty.pt`:
```bash
curl -L --fail \
https://huggingface.co/milchstrasse/SURE-Map/resolve/main/uncertainty.pt \
-o checkpoints/uncertainty.pt
```
Download the backbone separately:
```bash
curl -L --fail \
https://huggingface.co/robbyant/lingbot-map/resolve/main/lingbot-map.pt \
-o checkpoints/lingbot.pt
```
The SURE-Map inference code constructs `FlowSigmaHead` and loads the checkpoint's `sigma_head` state dictionary. Use the repository's inference and evaluation entry points rather than a Transformers `from_pretrained` call.
For example, after preparing KITTI and setting `dataset.root` in `online/configs/kitti.yaml`:
```bash
python online/run_kitti.py --config online/configs/kitti.yaml
```
See the [code repository](https://github.com/RCL-Robotics/SURE-map) for Oxford Spires, VBR, Neural RGB-D, 7-Scenes, and DTU preparation and evaluation instructions. This checkpoint is provided for the documented LingBot-Map-based configuration; compatibility with other backbones is not established.
## Citation
```bibtex
@misc{liu2026suremapselfcorrectingstreaminggeometric,
title = {SURE-Map: Self-Correcting Streaming Geometric Foundation Models},
author = {Mingkai Liu and Hao Zhao and Xingxing Zuo},
year = {2026},
eprint = {2609.15795},
archivePrefix = {arXiv},
primaryClass = {cs.CV},
url = {https://arxiv.org/abs/2609.15795}
}
```
## Licensing
The upstream repository licenses its original source code under Apache-2.0 and preserves separate licenses for third-party components. It does not explicitly state a separate license for this checkpoint. See the upstream [license information](https://github.com/RCL-Robotics/SURE-map#license).
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