Anchor3R: Streaming 3D Reconstruction with Transient Anchors for Long-Horizon Visual Mapping

• URL: http://arxiv.org/abs/2606.05035v1
• Date: Wed, 03 Jun 2026 16:00:13 GMT
• Title: Anchor3R: Streaming 3D Reconstruction with Transient Anchors for Long-Horizon Visual Mapping
• Abstract summary: Long-horizon online visual mapping is a core capability for robot perception.<n>Recent feed-forward 3D reconstruction models predict poses in a fixed coordinate system tied to the first frame or a persistent scene memory.<n>We propose emphAnchor3R, a streaming 3D reconstruction framework that treats feed-forward reconstruction as current-centric local measurement prediction.
• Score: 28.6268034980389
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Long-horizon online visual mapping is a core capability for robot perception, requiring continuous camera-motion and scene-geometry estimation from visual streams under bounded memory and computation. Recent feed-forward 3D reconstruction models provide strong geometric priors, but their streaming variants often predict poses in a fixed coordinate system tied to the first frame or a persistent scene memory. This fixed-gauge design leads to train--test mismatch, attention bias toward early anchors, and accumulated drift on sequences much longer than those seen during training. We propose \emph{Anchor3R}, a streaming 3D reconstruction framework that treats feed-forward reconstruction as current-centric local measurement prediction rather than persistent global-gauge regression. At each time step, Anchor3R predicts window-relative poses and a local pointmap in the current-frame coordinate system, turning streaming reconstruction into relative-pose measurement generation. These measurements support online pose updates, while loop-closure reinsertion and motion averaging align the trajectory and transform local pointmaps into a coherent global reconstruction. Experiments on indoor, outdoor, driving, and RGB-D benchmarks show that Anchor3R improves long-horizon pose accuracy and dense reconstruction quality over existing streaming baselines, while supporting bounded-memory online inference.

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