overthereality.ai↗

OVER RESEARCH

Open Science for Spatial Intelligence and Physical AI

We publish our work in the open — papers, datasets and models built on the world's largest 3D map. Our research spans Large Geospatial Models, machine perception and spatial intelligence, bridging real-world 3D data and the AI systems that will act in the physical world.

Research Note Jul 31, 2026 360° ReconstructionLIDARBenchmark

How Accurate Is Our Automatic 360°-Camera Reconstruction Pipeline?

Benchmarking the OVR 360° Pipeline Against a Simultaneous LIDAR Survey of the Same Site

OVER Research

We rode a LIDAR scanner and our 360° camera on the same pole through a 40 × 25 m site and compared the two reconstructions point by point: median surface agreement of 3.9 cm — at the reference scanner's own declared accuracy — drift-free geometry over the 118 m path, and one uniform 2.9% scale disagreement that the measurement chain traces to the metric reference rather than the reconstruction, removable with a single scalar.

Read the note↗ Validation code (GitHub)↗ Aligned clouds (PLY, 623 MB)↗
Research Note Jul 31, 2026 LGMMachine PerceptionFine-Tuning

Can 1,000 Open Scenes Make a State-of-the-Art 3D Model Better?

Assessing the OVER Dataset by Fine-Tuning a 3D Foundation Model on Its Open Sample

OVER Research

An empirical assessment of the OVER dataset for research, run entirely on OverMaps-1k — the open 1,000-scene sample anyone can download from Hugging Face: pose accuracy improves visibly on our domain, catastrophic forgetting is measured and defused through WiSE weight merging, and a scaling analysis shows how much data the gain requires.

Read the note↗ OverMaps-1k↗
Technical Report DatasetLGMMachine Perception

The OVER 3D Maps Dataset

Internet-Scale Real-World 3D Data for Training Large Geospatial Models

OVER Research

A technical overview of the OVER 3D Maps Dataset: 270K+ real-world indoor and outdoor locations with 100M+ images, depth maps and metric scaling data — orders of magnitude larger than the datasets powering current Vision Foundation Models, and built for training Large Geospatial Models.

Technical Report↗ Project Page↗
Open Dataset DatasetOpen Source

OverMaps-1k

An Open Dataset of 1,000 Real-World 3D Maps

OVER Research

An open-source sample of the OVER 3D Maps Dataset released on Hugging Face: 1,000 real-world 3D maps with multi-view images, depth and metric scale, ready for benchmarking visual relocalization, depth estimation and 3D reconstruction models.

Hugging Face↗ Project Page↗
Open Source

Code, models and data

Everything we release lives on GitHub and Hugging Face — follow along, open issues, build with us.

GitHub

OVR-Platform — SDKs, tools and research code.
Hugging Face

OverTheReality — open datasets and model releases.

Built on the OVER 3D Maps Dataset

Our research is grounded in the same dataset that powers the OVER network: hundreds of thousands of real-world 3D maps with images, depth and metric scale. Learn how it enables Large Geospatial Models and machine perception at scale.

Large Geospatial Models Research Collaborations