| title | Revisiting Local Context for Long-Horizon Streaming 3D Reconstruction |
|---|---|
| authors | Jiarong Han, Jincheng Xiong, Yuzhou Liu, Linzhe Shi, Changjie Wu, Ning Guo, Mu Xu, Hang Zhang, Ming Qian |
| date | 2026-08-27 |
| venue | arXiv (preprint, not peer reviewed) |
| id | arXiv:2608.27529 |
| affiliation | Alibaba AMAP CV Lab |
| upvotes | 30 (Hugging Face Daily Papers, 2026-11-01) |
| links | abs pdf hf code |
| abstract | Streaming 3D reconstruction from extremely long videos requires estimating camera motion and scene geometry online under bounded memory and computation. Early streaming models achieve causal, bounded-cost inference using finite context buffers or compact recurrent states, yet their estimates often deteriorate as sequences grow. Recent methods improve long-horizon stability by coupling short-range context with persistent or multi-level long-range memory. We pursue a different route: we keep the learned temporal state strictly local and formulate predictions whose targets remain independent of sequence length. We present ABot-Recon, a simple streaming model that caches KV features from only the preceding 11 frames. It predicts a point map in the current camera coordinate system together with an adjacent-frame relative pose. These predictions remain equivariant under changes of reference frame, and global poses and geometry are recovered through sequential composition. To reduce accumulated drift, a lightweight temporal refiner improves relative rotations using recent visual and motion context, while a composition-aware pose loss supervises multi-step pose composition. Extensive evaluations on challenging long-sequence benchmarks demonstrate the superior long-horizon performance of our local-context approach. On Oxford Spires, ABot-Recon achieves an ATE of 4.35 m and an RPE-R of 0.12^circ, reducing both errors by approximately 40\% relative to the best prior results. |
cite
@misc{han2026revisiting,
title={Revisiting Local Context for Long-Horizon Streaming 3D Reconstruction},
author={Jiarong Han and Jincheng Xiong and Yuzhou Liu and Linzhe Shi and Changjie Wu and Ning Guo and Mu Xu and Hang Zhang and Ming Qian},
year={2026},
eprint={2608.27529},
archivePrefix={arXiv},
url={https://arxiv.org/abs/2608.27529}
}