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Our product team walks through the full journey: Capture → Reconstruct → Localize Scaniverse creates high-fidelity 3D inputs from the real world—built for reconstruction, localization, and semantic understanding. Watch the full YouTube playlist: #NianticSpatial #Scaniverse #Reconstruction #VPS #GeospatialAI #AI #PhysicalAI

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Niantic Spatial 🌎

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10,949 просмотров • 4 месяцев назад •via X (Twitter)

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How do you go from scanning a real-world space → using it in an app, workflow, or environment? Our product team walks through Scaniverse step-by-step, from capturing spaces to generating production-ready 3D assets and enabling precise, real-world positioning. In the first video, Senior Product Manager, Bec Maxworth, walks through your entry point into Scaniverse from signing up to getting started so you can start building high-fidelity 3D models in minutes. Dive into the full walkthrough here: #NianticSpatial #Scaniverse #Reconstruction #VPS #GeospatialAI #AI #PhysicalAI
0:31

How do you go from scanning a real-world space → using it in an app, workflow, or environment? Our product team walks through Scaniverse step-by-step, from capturing spaces to generating production-ready 3D assets and enabling precise, real-world positioning. In the first video, Senior Product Manager, Bec Maxworth, walks through your entry point into Scaniverse from signing up to getting started so you can start building high-fidelity 3D models in minutes. Dive into the full walkthrough here: #NianticSpatial #Scaniverse #Reconstruction #VPS #GeospatialAI #AI #PhysicalAI

Niantic Spatial 🌎

10,739 просмотров • 4 месяцев назад

Construction sites change fast. Constant site revisits are expensive and time-consuming. With Scaniverse, teams can capture and operationalize real-world environments with precision at scale using high-fidelity textured meshes and Gaussian splats. Monitor progress remotely, improve collaboration, document site conditions, and reduce unnecessary visits — all from a phone or 360° camera. Sign up for Scaniverse today and begin to #SplatYourWorld. #NianticSpatial #Scaniverse #VPS #GeospatialAI #AI #GaussianSplat #Reconstruction #PhysicalAI
0:23

Construction sites change fast. Constant site revisits are expensive and time-consuming. With Scaniverse, teams can capture and operationalize real-world environments with precision at scale using high-fidelity textured meshes and Gaussian splats. Monitor progress remotely, improve collaboration, document site conditions, and reduce unnecessary visits — all from a phone or 360° camera. Sign up for Scaniverse today and begin to #SplatYourWorld. #NianticSpatial #Scaniverse #VPS #GeospatialAI #AI #GaussianSplat #Reconstruction #PhysicalAI

Niantic Spatial 🌎

16,635 просмотров • 3 месяцев назад

🌎 The world in your pocket, now in 3D. For a limited time, upgrade to a Scaniverse Annual Plan by June 30 and get: ✅12 months for the price of 10 + up to 105,000 bonus cloud processing credits. ⏰Upgrade today! #NianticSpatial #Scaniverse #Reconstruction #3DScanning #GaussianSplat #360Capture #DigitalTwin #AI #GeospatialAI #PhysicalAI #VPS
0:29

🌎 The world in your pocket, now in 3D. For a limited time, upgrade to a Scaniverse Annual Plan by June 30 and get: ✅12 months for the price of 10 + up to 105,000 bonus cloud processing credits. ⏰Upgrade today! #NianticSpatial #Scaniverse #Reconstruction #3DScanning #GaussianSplat #360Capture #DigitalTwin #AI #GeospatialAI #PhysicalAI #VPS

Niantic Spatial 🌎

11,326 просмотров • 2 месяцев назад

📲💻Capture and scan with Scaniverse, then bring your sites directly into NSDK 4.0. A unified spatial data pipeline connects capture → reconstruction → localization → runtime—so your scans are immediately usable in your XR projects. Build with Unity, Swift, Kotlin, and early ROS2 support, and deploy high-performance experiences across mobile and robotic systems within your existing workflows. 🔗Get started today: #NianticSpatial #Scaniverse #NDSK #GeospatialAI #PhysicalAI #AI #XR #VR #Robotics #Unity #Kotlin #Swift
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📲💻Capture and scan with Scaniverse, then bring your sites directly into NSDK 4.0. A unified spatial data pipeline connects capture → reconstruction → localization → runtime—so your scans are immediately usable in your XR projects. Build with Unity, Swift, Kotlin, and early ROS2 support, and deploy high-performance experiences across mobile and robotic systems within your existing workflows. 🔗Get started today: #NianticSpatial #Scaniverse #NDSK #GeospatialAI #PhysicalAI #AI #XR #VR #Robotics #Unity #Kotlin #Swift

Niantic Spatial 🌎

10,781 просмотров • 4 месяцев назад

SPZ 4 is here. 🚀 3–5x faster encoding. 2x faster loading. 20x faster in the browser. Tens of millions of points, no sweat. The "JPG for 3D Gaussian splats" just leveled up. Big thanks to everyone who made this release happen, especially the team at Adobe. Read more: #NianticSpatial #Scaniverse #SPZ #GaussianSplat #Reconstruction #PhysicalAI #GeospatialAI #AI #Adobe
0:25

SPZ 4 is here. 🚀 3–5x faster encoding. 2x faster loading. 20x faster in the browser. Tens of millions of points, no sweat. The "JPG for 3D Gaussian splats" just leveled up. Big thanks to everyone who made this release happen, especially the team at Adobe. Read more: #NianticSpatial #Scaniverse #SPZ #GaussianSplat #Reconstruction #PhysicalAI #GeospatialAI #AI #Adobe

Niantic Spatial 🌎

63,648 просмотров • 3 месяцев назад

Today, Niantic Spatial introduces Scaniverse — our flagship product and the gateway to our spatial intelligence platform and Large Geospatial Model. Here’s what’s new: 🔹Scaniverse (iOS mobile + web): Capture once, generate multiple outputs—VPS maps, meshes, and Gaussian splats (Android coming soon) 🔹Collaborative mapping: Multi-user scans fused into a single, continuously improving model 🔹 On-device validation: Preview VPS coverage and test localization in real time 🔹VPS 2.0: Global-scale positioning—centimeter-accurate where mapped, reliable everywhere else (even where GPS fails) 🔹NSDK 4.0 (coming soon): A unified SDK across Unity, Swift, Android, and ROS 2 Read more: #NianticSpatial #Scaniverse #VPS #GeospatialAI #AI
1:00

Today, Niantic Spatial introduces Scaniverse — our flagship product and the gateway to our spatial intelligence platform and Large Geospatial Model. Here’s what’s new: 🔹Scaniverse (iOS mobile + web): Capture once, generate multiple outputs—VPS maps, meshes, and Gaussian splats (Android coming soon) 🔹Collaborative mapping: Multi-user scans fused into a single, continuously improving model 🔹 On-device validation: Preview VPS coverage and test localization in real time 🔹VPS 2.0: Global-scale positioning—centimeter-accurate where mapped, reliable everywhere else (even where GPS fails) 🔹NSDK 4.0 (coming soon): A unified SDK across Unity, Swift, Android, and ROS 2 Read more: #NianticSpatial #Scaniverse #VPS #GeospatialAI #AI

Niantic Spatial 🌎

119,029 просмотров • 4 месяцев назад

Physical AI needs more than maps, GPS, or pixels alone. It needs a living, geometrically accurate understanding of the real world. Niantic Spatial and Spexi are partnering to transform drone imagery into large-scale 3D intelligence for physical AI. 🔗Learn more: #NianticSpatial #Spexi #PhysicalAI #Reconstruction #GaussianSplat #DigitalTwins #Robotics #GeospatialAI #AI #GeospatialIntelligence #GEOINT #SpatialIntelligence
0:59

Physical AI needs more than maps, GPS, or pixels alone. It needs a living, geometrically accurate understanding of the real world. Niantic Spatial and Spexi are partnering to transform drone imagery into large-scale 3D intelligence for physical AI. 🔗Learn more: #NianticSpatial #Spexi #PhysicalAI #Reconstruction #GaussianSplat #DigitalTwins #Robotics #GeospatialAI #AI #GeospatialIntelligence #GEOINT #SpatialIntelligence

Niantic Spatial 🌎

27,988 просмотров • 3 месяцев назад

Your best Gaussian Splat might already be sitting in your Scaniverse account. The #SplatYourWorld Challenge is open through July 31. Submit your best capture for a chance to win a share of $4,000 USD in prizes. We're looking for standout 3D reconstructions of: 🏭 Industrial environments 🌲 Natural landscapes 🏙️ Urban infrastructure No need to create something new—just submit your best Gaussian Splat and put the prize money toward new gear, more captures, or whatever powers your workflow. 📅 Deadline: July 31, 11:59 PM PT Learn more: #NianticSpatial #3DReconstruction #DigitalTwins #PhysicalAI #GeospatialAI #AI #3DGS
0:26

Your best Gaussian Splat might already be sitting in your Scaniverse account. The #SplatYourWorld Challenge is open through July 31. Submit your best capture for a chance to win a share of $4,000 USD in prizes. We're looking for standout 3D reconstructions of: 🏭 Industrial environments 🌲 Natural landscapes 🏙️ Urban infrastructure No need to create something new—just submit your best Gaussian Splat and put the prize money toward new gear, more captures, or whatever powers your workflow. 📅 Deadline: July 31, 11:59 PM PT Learn more: #NianticSpatial #3DReconstruction #DigitalTwins #PhysicalAI #GeospatialAI #AI #3DGS

Niantic Spatial 🌎

27,130 просмотров • 1 месяц назад

More and more users are turning their 360 footage into fully explorable 3D Gaussian Splats with View it here: This reconstruction started from a simple capture and is now a fully explorable 3D Gaussian Splat rendered in the FreeGaussian viewer, complete with point cloud reconstruction and high-fidelity spatial detail. More and more creators are discovering that their existing footage can become immersive 3D scenes. And they’re doing it for free with FreeGaussian
0:58

More and more users are turning their 360 footage into fully explorable 3D Gaussian Splats with View it here: This reconstruction started from a simple capture and is now a fully explorable 3D Gaussian Splat rendered in the FreeGaussian viewer, complete with point cloud reconstruction and high-fidelity spatial detail. More and more creators are discovering that their existing footage can become immersive 3D scenes. And they’re doing it for free with FreeGaussian

Over the Reality 🌐

14,803 просмотров • 3 месяцев назад

📢 Lyra: Generative 3D Scene Reconstruction via Video Diffusion Model Self-Distillation Got only one or a few images and wondering if recovering the 3D environment is a reconstruction or generation problem? Why not do it with a generative reconstruction model! We show that a camera-conditioned video diffusion model can be transformed into a generative reconstruction model that directly outputs a high-quality 3D Gaussian Splatting representation through self-distillation, without requiring real-world training data. Check out our results in the video (wait for dynamic scenes in the second half!) : Project Page: Code and Models: Paper:
0:50

📢 Lyra: Generative 3D Scene Reconstruction via Video Diffusion Model Self-Distillation Got only one or a few images and wondering if recovering the 3D environment is a reconstruction or generation problem? Why not do it with a generative reconstruction model! We show that a camera-conditioned video diffusion model can be transformed into a generative reconstruction model that directly outputs a high-quality 3D Gaussian Splatting representation through self-distillation, without requiring real-world training data. Check out our results in the video (wait for dynamic scenes in the second half!) : Project Page: Code and Models: Paper:

Sherwin Bahmani

66,722 просмотров • 11 месяцев назад

📢📢GenRecon: Bridging Generative Priors for Multi-View 3D Scene Reconstruction📢📢 Reconstructing high-fidelity 3D scenes from sparse RGB input is hard. It needs a strong 3D prior! We reformulate multi-view scene reconstruction as conditional 3D generation over overlapping spatial chunks, lifting posed image features into a generative shape prior via 3D conditioning. As an example prior, we build on Trellis2, and train it such that its reconstruction is pixel aligned and matches from all views. GenRecon achieves unprecedented reconstruction quality from any sparse RGB input sequence, even from a phone capture. The reconstruction also includes PBR materials which facilitates relighting and virtual object insertion. Amazing work by Katharina Schmid, Nicolas von Lützow, Jozef, Angela Dai
0:26

📢📢GenRecon: Bridging Generative Priors for Multi-View 3D Scene Reconstruction📢📢 Reconstructing high-fidelity 3D scenes from sparse RGB input is hard. It needs a strong 3D prior! We reformulate multi-view scene reconstruction as conditional 3D generation over overlapping spatial chunks, lifting posed image features into a generative shape prior via 3D conditioning. As an example prior, we build on Trellis2, and train it such that its reconstruction is pixel aligned and matches from all views. GenRecon achieves unprecedented reconstruction quality from any sparse RGB input sequence, even from a phone capture. The reconstruction also includes PBR materials which facilitates relighting and virtual object insertion. Amazing work by Katharina Schmid, Nicolas von Lützow, Jozef, Angela Dai

Matthias Niessner

18,204 просмотров • 3 месяцев назад

Physical AI for defense and intelligence starts with an accurate model of the world – high-fidelity, geometrically grounded, built for the environments where it actually matters. Today, Niantic Spatial 🌎 is awardable on the Department of War 🇺🇸’s Tradewinds Solutions Marketplace for 3D Reconstruction, our second capability to clear that bar after Visual Positioning, announced earlier this month. Together they deliver two critical layers of the spatial stack: high-fidelity 3D models of contested environments, and precise location within them; a foundation for mission-critical operations that need to visualize and navigate the physical world. The capability is ready. The procurement path is open.
0:24

Physical AI for defense and intelligence starts with an accurate model of the world – high-fidelity, geometrically grounded, built for the environments where it actually matters. Today, Niantic Spatial 🌎 is awardable on the Department of War 🇺🇸’s Tradewinds Solutions Marketplace for 3D Reconstruction, our second capability to clear that bar after Visual Positioning, announced earlier this month. Together they deliver two critical layers of the spatial stack: high-fidelity 3D models of contested environments, and precise location within them; a foundation for mission-critical operations that need to visualize and navigate the physical world. The capability is ready. The procurement path is open.

asim ᯅ

14,288 просмотров • 3 месяцев назад

Most digital twin investments stall for one reason: They’re not grounded in how the world actually looks today. Niantic Spatial’s Reconstruction capability fixes this, creating a living, machine-readable 3D model that stays in sync with reality, so every system, team, and workflow operates from the same ground truth. In a new blog by Trista Pierce, Business Development Lead, explore how Scaniverse’s Reconstruction technology changes the cadence entirely. Read more:
0:35

Most digital twin investments stall for one reason: They’re not grounded in how the world actually looks today. Niantic Spatial’s Reconstruction capability fixes this, creating a living, machine-readable 3D model that stays in sync with reality, so every system, team, and workflow operates from the same ground truth. In a new blog by Trista Pierce, Business Development Lead, explore how Scaniverse’s Reconstruction technology changes the cadence entirely. Read more:

Niantic Spatial 🌎

418,390 просмотров • 4 месяцев назад

for physical AI to work in the real world, it needs high-fidelity 3D models of the real world. not just for visualization — for localization, spatial reasoning, and real-to-sim workflows that close the gap between training and deployment. at Niantic Spatial 🌎, we're turning Spexi drone imagery into exactly that — city-scale Gaussian splats grounded in the environments that matter most.
1:00

for physical AI to work in the real world, it needs high-fidelity 3D models of the real world. not just for visualization — for localization, spatial reasoning, and real-to-sim workflows that close the gap between training and deployment. at Niantic Spatial 🌎, we're turning Spexi drone imagery into exactly that — city-scale Gaussian splats grounded in the environments that matter most.

asim ᯅ

49,478 просмотров • 2 месяцев назад

📢📢 𝐏𝐞𝐫𝐜𝐇𝐞𝐚𝐝: 𝐏𝐞𝐫𝐜𝐞𝐩𝐭𝐮𝐚𝐥 𝐇𝐞𝐚𝐝 𝐌𝐨𝐝𝐞𝐥 𝐟𝐨𝐫 𝐒𝐢𝐧𝐠𝐥𝐞-𝐈𝐦𝐚𝐠𝐞 𝟑𝐃 𝐇𝐞𝐚𝐝 𝐑𝐞𝐜𝐨𝐧𝐬𝐭𝐫𝐮𝐜𝐭𝐢𝐨𝐧 & 𝐄𝐝𝐢𝐭𝐢𝐧𝐠📢📢 PercHead reconstructs realistic 3D heads from a single image and enables disentangled 3D editing via geometric controls and style inputs from images or text. At its core is a generalized 3D head decoder trained with perceptual supervision from DINOv2 and SAM 2.1. We find that our new perceptual loss formulation improves reconstruction fidelity compared to commonly-used methods such as LPIPS. Our trained reconstruction model is able to generate 3D-consistent heads from a single input image. Even with challenging side-view inputs, the model robustly infers missing regions for a coherent, high-fidelity output. In addition, our architecture seamlessly adapts to downstream tasks: by swapping the encoder, we can transform the model into a disentangled 3D editing pipeline. In this scenario, we can control geometry through - potentially hand-drawn - segmentation maps, and condition style via image or text prompt. We also provide an interactive GUI to enable the exploration of our editing pipeline. 🌍 📽️ Great work by Antonio Oroz and Tobias Kirschstein
0:30

📢📢 𝐏𝐞𝐫𝐜𝐇𝐞𝐚𝐝: 𝐏𝐞𝐫𝐜𝐞𝐩𝐭𝐮𝐚𝐥 𝐇𝐞𝐚𝐝 𝐌𝐨𝐝𝐞𝐥 𝐟𝐨𝐫 𝐒𝐢𝐧𝐠𝐥𝐞-𝐈𝐦𝐚𝐠𝐞 𝟑𝐃 𝐇𝐞𝐚𝐝 𝐑𝐞𝐜𝐨𝐧𝐬𝐭𝐫𝐮𝐜𝐭𝐢𝐨𝐧 & 𝐄𝐝𝐢𝐭𝐢𝐧𝐠📢📢 PercHead reconstructs realistic 3D heads from a single image and enables disentangled 3D editing via geometric controls and style inputs from images or text. At its core is a generalized 3D head decoder trained with perceptual supervision from DINOv2 and SAM 2.1. We find that our new perceptual loss formulation improves reconstruction fidelity compared to commonly-used methods such as LPIPS. Our trained reconstruction model is able to generate 3D-consistent heads from a single input image. Even with challenging side-view inputs, the model robustly infers missing regions for a coherent, high-fidelity output. In addition, our architecture seamlessly adapts to downstream tasks: by swapping the encoder, we can transform the model into a disentangled 3D editing pipeline. In this scenario, we can control geometry through - potentially hand-drawn - segmentation maps, and condition style via image or text prompt. We also provide an interactive GUI to enable the exploration of our editing pipeline. 🌍 📽️ Great work by Antonio Oroz and Tobias Kirschstein

Matthias Niessner

18,885 просмотров • 9 месяцев назад

Another city. Another full 3D Gaussian Splat reconstruction. This entire neighborhood was captured while walking with an Insta360 X5, then processed with our GPU pipeline and transformed into a high-fidelity, machine-readable 3D environment with Over the Reality. What you’re seeing is not an isolated virtual world. It’s a 3D digital twin of a real-world location, built from structured spatial data where every building, street, and detail can become usable by AI, robotics, and XR. And it’s happening at scale, across cities in more than 180 countries every day. Have an Insta360 X5 and want to become a mapper? Apply here: Want to build a 3D Gaussian Splat from a video you already recorded? Do it for free at powered by Over the Reality.
2:42

Another city. Another full 3D Gaussian Splat reconstruction. This entire neighborhood was captured while walking with an Insta360 X5, then processed with our GPU pipeline and transformed into a high-fidelity, machine-readable 3D environment with Over the Reality. What you’re seeing is not an isolated virtual world. It’s a 3D digital twin of a real-world location, built from structured spatial data where every building, street, and detail can become usable by AI, robotics, and XR. And it’s happening at scale, across cities in more than 180 countries every day. Have an Insta360 X5 and want to become a mapper? Apply here: Want to build a 3D Gaussian Splat from a video you already recorded? Do it for free at powered by Over the Reality.

Over the Reality 🌐

400,097 просмотров • 4 месяцев назад

🏛️The Musée national des Monuments Français preserves centuries of history. In many ways, #Scaniverse is becoming a museum for the world—helping anyone preserve places, landmarks, and moments as explorable 3D Gaussian Splats. Love seeing how much sharper and more photorealistic the latest reconstructions are. Even distant backgrounds, text, and fine details have improved noticeably. ✨ Have an amazing reality capture to share? Enter the #SplatYourWorld Challenge by July 31 for a chance to win a share of $4,000 USD. #GaussianSplats #3DGS #RealityCapture #AI
0:32

🏛️The Musée national des Monuments Français preserves centuries of history. In many ways, #Scaniverse is becoming a museum for the world—helping anyone preserve places, landmarks, and moments as explorable 3D Gaussian Splats. Love seeing how much sharper and more photorealistic the latest reconstructions are. Even distant backgrounds, text, and fine details have improved noticeably. ✨ Have an amazing reality capture to share? Enter the #SplatYourWorld Challenge by July 31 for a chance to win a share of $4,000 USD. #GaussianSplats #3DGS #RealityCapture #AI

Niantic Spatial 🌎

23,343 просмотров • 1 месяц назад

Large-scale Gaussian splats have reached a new level of realism. This is a well-known temple in Bangkok, reconstructed as a high-fidelity 3D environment from 360 captures. At this level, the boundary between video and 3D starts to disappear. But what you’re looking at is not a video. It’s a dense spatial representation of a real place, where geometry, texture, and structure are preserved and made machine-readable. This kind of 3D data can power Visual AI, Robotics navigation, VPS localization, XR experiences, world models, and next-generation spatial computing systems. Built with Over the Reality.
2:46

Large-scale Gaussian splats have reached a new level of realism. This is a well-known temple in Bangkok, reconstructed as a high-fidelity 3D environment from 360 captures. At this level, the boundary between video and 3D starts to disappear. But what you’re looking at is not a video. It’s a dense spatial representation of a real place, where geometry, texture, and structure are preserved and made machine-readable. This kind of 3D data can power Visual AI, Robotics navigation, VPS localization, XR experiences, world models, and next-generation spatial computing systems. Built with Over the Reality.

Over the Reality 🌐

347,340 просмотров • 3 месяцев назад