ExplorerComputer VisionComputer Vision
Research PaperResearchia:202605.27005

G3T Up! Gravity Aligned Coordinate Frames Simplify Pointmap Processing

Bharath Raj Nagoor Kani

Abstract

Modern feed-forward 3D reconstruction methods like VGGT predict pixel-aligned pointmaps in camera-centric coordinate frames. However, this choice of coordinate frame is not always optimal. We propose instead to predict pointmaps in upright, gravity-aligned frames that exploit strong structural cues present in many real-world scenes. Unlike camera-centric frames, gravity-aligned frames share a common vertical axis across viewpoints, reducing the rotational degrees of freedom needed to relate poin...

Submitted: May 27, 2026Subjects: Computer Vision; Computer Vision

Description / Details

Modern feed-forward 3D reconstruction methods like VGGT predict pixel-aligned pointmaps in camera-centric coordinate frames. However, this choice of coordinate frame is not always optimal. We propose instead to predict pointmaps in upright, gravity-aligned frames that exploit strong structural cues present in many real-world scenes. Unlike camera-centric frames, gravity-aligned frames share a common vertical axis across viewpoints, reducing the rotational degrees of freedom needed to relate pointmaps to one another. To this end, we introduce the Gravity Grounded Geometry Transformer (G3T), fine-tuned from existing models on gravity-aligned 3D data. G3T produces highly accurate gravity-aware predictions, including upright pointmaps and camera-to-gravity poses. We further introduce G3T-Long, a submap-based incremental 3D reconstruction pipeline that leverages the reduced rotational degrees of freedom afforded by upright frames to achieve significantly improved reconstruction accuracy.


Source: arXiv:2605.27372v1 - http://arxiv.org/abs/2605.27372v1 PDF: https://arxiv.org/pdf/2605.27372v1 Original Link: http://arxiv.org/abs/2605.27372v1

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Date:
May 27, 2026
Topic:
Computer Vision
Area:
Computer Vision
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