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---
license: apache-2.0
pipeline_tag: image-to-3d
---
# ABot-Recon
ABot-Recon is a streaming 3D reconstruction model that estimates camera motion and scene geometry online from extremely long videos using only a fixed local context of 12 frames. It predicts a point map in the current camera coordinate system and an adjacent-frame relative pose, then composes these local predictions into a global reconstruction through sequential composition.
**Paper:** [Revisiting Local Context for Long-Horizon Streaming 3D Reconstruction](https://arxiv.org/abs/2608.27529)
**Project page:** [ABot-Recon](https://amap-cvlab.github.io/ABot-Recon-html/)
**Code:** [github.com/amap-cvlab/ABot-Recon](https://github.com/amap-cvlab/ABot-Recon)
## Quick Start
```python
from pathlib import Path
from abot_recon import ABotRecon
images = sorted(Path("examples/images").glob("*.jpg"))
model = ABotRecon.from_pretrained(
"acvlab/ABot-Recon",
device="cuda",
attention_backend="auto",
loop_closure=False,
)
result = model.infer(images)
trajectory = result.camera_poses
relative_poses = result.relative_poses
local_points = result.local_points
confidence = result.confidence
```
For a full description of usage options, please refer to the [GitHub README](https://github.com/amap-cvlab/ABot-Recon).

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