metadata
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
Project page: ABot-Recon
Code: github.com/amap-cvlab/ABot-Recon
Quick Start
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.