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3d visual positioning experiment -- look at the alignment between the 3d mesh and the live camera view. Truly feels magical -- like x-ray vision. Workflow: 1. Scanned a street in 15 mins w/ xgrids 2. Localized against that scan at night, in real-time, while sitting in a car... show more

Bilawal Sidhu

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27,278 görüntüleme • 8 ay önce •via X (Twitter)

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$Late Xmas gift from XGRIDS has arrived! LiDAR SLAM + RGB cameras to create massive 3D Gaussian Splats in a fraction of time as my DSLR rig. Look out for tests in the new year! For now back to kicking it with the fam.$

Late Xmas gift from XGRIDS has arrived! LiDAR SLAM + RGB cameras to create massive 3D Gaussian Splats in a fraction of time as my DSLR rig. Look out for tests in the new year! For now back to kicking it with the fam.

Bilawal Sidhu

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🇨🇭 This flying robot goes where humans refuse to. The Elios 3 is built for extremely dangerous and confined spaces, with a protective cage that lets it smash into walls, recover, and keep flying. While exploring, it uses onboard LiDAR to build detailed 3D maps in real time. This is next-level inspection tech. Writer: Val

🇨🇭 This flying robot goes where humans refuse to. The Elios 3 is built for extremely dangerous and confined spaces, with a protective cage that lets it smash into walls, recover, and keep flying. While exploring, it uses onboard LiDAR to build detailed 3D maps in real time. This is next-level inspection tech. Writer: Val

Mario Nawfal

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Excited to share this demo from Over the Reality! Watch our Unitree Go2 robodog navigating our office while reconstructing the 3D space in real-time using the VGGT-based foundation vision model. This is a prime example of machine perception in action, turning raw RGB camera feeds into rich, detailed 3D maps! The robodog's RGB cam generates a dense, textured 3D reconstruction via VGGT from a few photograms, capturing nuances like object shapes and surfaces with impressive fidelity (main view). Compare that to the standard LiDAR system (top right), it's sparser, more point-cloud focused, lacking the visual richness. Vision models are closing the gap fast! What's powering this? VGGT, a cutting-edge foundation model for 3D perception, trained on datasets orders of magnitude smaller than our massive OVER 3D maps dataset. Imagine the leap when we apply OVER's scale to VGGT-like transformer based architectures, denser reconstructions, better generalization, revolutionary for robotics, machine perception & AR! Stay tuned for more breakthroughs at the intersection of AI, robotics, and DePIN. We're building the future of Physical AI and Spatial Computing at Over the Reality 🌐 What do you think, ready for robodogs in your world? Drop your thoughts! 🤖🌐

Excited to share this demo from Over the Reality! Watch our Unitree Go2 robodog navigating our office while reconstructing the 3D space in real-time using the VGGT-based foundation vision model. This is a prime example of machine perception in action, turning raw RGB camera feeds into rich, detailed 3D maps! The robodog's RGB cam generates a dense, textured 3D reconstruction via VGGT from a few photograms, capturing nuances like object shapes and surfaces with impressive fidelity (main view). Compare that to the standard LiDAR system (top right), it's sparser, more point-cloud focused, lacking the visual richness. Vision models are closing the gap fast! What's powering this? VGGT, a cutting-edge foundation model for 3D perception, trained on datasets orders of magnitude smaller than our massive OVER 3D maps dataset. Imagine the leap when we apply OVER's scale to VGGT-like transformer based architectures, denser reconstructions, better generalization, revolutionary for robotics, machine perception & AR! Stay tuned for more breakthroughs at the intersection of AI, robotics, and DePIN. We're building the future of Physical AI and Spatial Computing at Over the Reality 🌐 What do you think, ready for robodogs in your world? Drop your thoughts! 🤖🌐

Over the Reality 🌐

359,717 görüntüleme • 10 ay önce

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.

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 🌐

347,044 görüntüleme • 2 ay önce

Instant Skinned Gaussian Avatars for Web, Mobile and VR Applications Short summary: In our system, we animate a background 3D mesh and have the Gaussian splats follow the mesh’s vertices. During preprocessing, splats are assigned to mesh vertices, and their relative transformations are stored. Once this data is saved, you can instantly use it in your applications without further preprocessing. At runtime, we animate the background 3D mesh, update the Gaussian splats in parallel, and resort all Gaussian splats every frame based on the viewer’s perspective.

Instant Skinned Gaussian Avatars for Web, Mobile and VR Applications Short summary: In our system, we animate a background 3D mesh and have the Gaussian splats follow the mesh’s vertices. During preprocessing, splats are assigned to mesh vertices, and their relative transformations are stored. Once this data is saved, you can instantly use it in your applications without further preprocessing. At runtime, we animate the background 3D mesh, update the Gaussian splats in parallel, and resort all Gaussian splats every frame based on the viewer’s perspective.

MrNeRF

66,016 görüntüleme • 9 ay önce

I made a cute 3D wizard in minutes... for free The combo was simple: Unbound + Tripo. Unbound helped me shape the character idea, then Tripo turned it into a 3D model without the usual heavy workflow. The whole process felt fast, playful, and easy to experiment with If you’re a 3D artist, a visual creator, or just starting to explore 3D, try Unbound while it’s still free for a limited time. You can use it to create characters, creatures, and 3D models without feeling overwhelmed I'm sure many visual creators are going to love this Link in the first comment 👇🏻

I made a cute 3D wizard in minutes... for free The combo was simple: Unbound + Tripo. Unbound helped me shape the character idea, then Tripo turned it into a 3D model without the usual heavy workflow. The whole process felt fast, playful, and easy to experiment with If you’re a 3D artist, a visual creator, or just starting to explore 3D, try Unbound while it’s still free for a limited time. You can use it to create characters, creatures, and 3D models without feeling overwhelmed I'm sure many visual creators are going to love this Link in the first comment 👇🏻

Amira Zairi

18,116 görüntüleme • 2 ay önce

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.

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 görüntüleme • 2 ay önce

📣 New research from GenAI at Meta, introducing Meta 3D Gen: A new system for end-to-end generation of 3D assets from text in <1min. Meta 3D Gen is a new combined AI system that can generate high-quality 3D assets, with both high-resolution textures and material maps end-to-end, producing results that are superior to existing solutions — at 3-10x the speed of existing work in this space. Details in the technical report ➡️

📣 New research from GenAI at Meta, introducing Meta 3D Gen: A new system for end-to-end generation of 3D assets from text in <1min. Meta 3D Gen is a new combined AI system that can generate high-quality 3D assets, with both high-resolution textures and material maps end-to-end, producing results that are superior to existing solutions — at 3-10x the speed of existing work in this space. Details in the technical report ➡️

AI at Meta

408,809 görüntüleme • 2 yıl önce

Apple Maps 3d is insanely impressive now (see video below) Google on the other hand decided to build an insanely clunky solution to display 3d maps to avoid using mobile GPUs: A Google server streams (!) a live video of its 3d rendered map to you, the result is a disastrous: a super laggy and clunky 3d view full of video compression artefacts with a response time of 2-3 seconds for every movement And I know WHY they built that, someone felt it was not inclusive to only have 3d maps that are high performing on iOS because Apple's GPUs are insanely fast and can deal with it (as you can see below in Apple Maps) but they wanted to support inferior phones, I get it But then they also decided to worsen the experience for iOS users who could easily run 3d natively on its GPU It's just an insane product decision, there's no way to cut it: they could have super smooth 3d like Apple Maps but neutered it with a clunky live stream Even more insane because Google does have native 3d on iOS in a completely different app that nobody uses: Google Earth Is 3d important? Not rly for nav no but it shows again something about Google's engineering decisions, like the redesign of the Google OAuth Login screen that made zero sense Nobody is speaking up against bad ideas in Google meetings, everyone's too scared of HR maybe, it's the opposite of a meritocracy and it's just super visible from using Google products right now

Apple Maps 3d is insanely impressive now (see video below) Google on the other hand decided to build an insanely clunky solution to display 3d maps to avoid using mobile GPUs: A Google server streams (!) a live video of its 3d rendered map to you, the result is a disastrous: a super laggy and clunky 3d view full of video compression artefacts with a response time of 2-3 seconds for every movement And I know WHY they built that, someone felt it was not inclusive to only have 3d maps that are high performing on iOS because Apple's GPUs are insanely fast and can deal with it (as you can see below in Apple Maps) but they wanted to support inferior phones, I get it But then they also decided to worsen the experience for iOS users who could easily run 3d natively on its GPU It's just an insane product decision, there's no way to cut it: they could have super smooth 3d like Apple Maps but neutered it with a clunky live stream Even more insane because Google does have native 3d on iOS in a completely different app that nobody uses: Google Earth Is 3d important? Not rly for nav no but it shows again something about Google's engineering decisions, like the redesign of the Google OAuth Login screen that made zero sense Nobody is speaking up against bad ideas in Google meetings, everyone's too scared of HR maybe, it's the opposite of a meritocracy and it's just super visible from using Google products right now

@levelsio

1,488,855 görüntüleme • 1 yıl önce

VPS or visual positioning system... this is how AR glasses and robots will understand where they are in the real world and know where to go. It’s also how you can spatially annotate reality with cm level accuracy - all using a machine readable model of the world.

VPS or visual positioning system... this is how AR glasses and robots will understand where they are in the real world and know where to go. It’s also how you can spatially annotate reality with cm level accuracy - all using a machine readable model of the world.

Bilawal Sidhu

27,965 görüntüleme • 7 ay önce

✨ Made a new mini feature on Photo AI: [ Grab from 3d model ] So the problem is we're at that stage in time (typical for AI) where image-to-3d models are not good enough but are fun to play with, but we know they'll be good enough in 1-2 years With [ Make 3d model ] you already can turn any Photo AI pic into a 3d model but it still looks hyper clunky and deformed, but it works! One cool idea I had to make that more useful and made now: Let people make a 3d model then change the view of the it with the 3d viewer, then press [ o ] and it grabs a frame of the 3d That image you can then [ Remix ] (img2img), and it becomes a real photo again and that in turn you can then turn into a video again with [ Make video ] So that essentially gives you a fully freeform camera position control to take photos with One thing I need to fix is the background/skybox, I kinda need to take the original photo and remove the person and just get the background for the 3d model viewer, in this case it should be white, but it's a start!

✨ Made a new mini feature on Photo AI: [ Grab from 3d model ] So the problem is we're at that stage in time (typical for AI) where image-to-3d models are not good enough but are fun to play with, but we know they'll be good enough in 1-2 years With [ Make 3d model ] you already can turn any Photo AI pic into a 3d model but it still looks hyper clunky and deformed, but it works! One cool idea I had to make that more useful and made now: Let people make a 3d model then change the view of the it with the 3d viewer, then press [ o ] and it grabs a frame of the 3d That image you can then [ Remix ] (img2img), and it becomes a real photo again and that in turn you can then turn into a video again with [ Make video ] So that essentially gives you a fully freeform camera position control to take photos with One thing I need to fix is the background/skybox, I kinda need to take the original photo and remove the person and just get the background for the 3d model viewer, in this case it should be white, but it's a start!

@levelsio

119,210 görüntüleme • 1 yıl önce

Claude Fable 5 vs Kimi K3 — same 3D build, 3.3x cheaper. someone prototyped a 3D stadium seat-view picker with Fable 5 — preview exactly what you'll see from your seat before buying a ticket. I rebuilt the same thing with Kimi K3 in two hours, at 3.3x lower cost. no more static seat maps. pick a seat, see the actual view in 3D, then buy. works for cinemas, concerts, cricket grounds, Wimbledon — any venue. K3 dropped this week: 2.8 trillion parameters, open weights July 27. 3D is the future, and it just got a lot cheaper to build. Live Fable 5: Live Kimi K3: Code: full Kimi K3 breakdown below.

Claude Fable 5 vs Kimi K3 — same 3D build, 3.3x cheaper. someone prototyped a 3D stadium seat-view picker with Fable 5 — preview exactly what you'll see from your seat before buying a ticket. I rebuilt the same thing with Kimi K3 in two hours, at 3.3x lower cost. no more static seat maps. pick a seat, see the actual view in 3D, then buy. works for cinemas, concerts, cricket grounds, Wimbledon — any venue. K3 dropped this week: 2.8 trillion parameters, open weights July 27. 3D is the future, and it just got a lot cheaper to build. Live Fable 5: Live Kimi K3: Code: full Kimi K3 breakdown below.

Kirill

205,380 görüntüleme • 7 gün önce

This is pretty cool 👓 Google Announces Geospatial Creator powered by ARCore & Google Maps and it allows you to visualize, design, and publish world-anchored content by using Unity ! Few features available: 📌 Photorealistic 3D Tiles: Visualize the 3D geometry of the world and deploy location-anchored content accurately with high-resolution, photorealistic 3D tiles. 📌 Geospatial anchors: Place and anchor 3D content at any given latitude, longitude, and altitude with sub-meter accuracy in areas covered by Google Street View. 📌 Terrain anchors: Place and anchor 3D content with only latitude and longitude coordinates, using data from Google Maps to determine ground level. 📌 Rooftop anchors: Use rooftops to place and anchor 3D content with respect to the building geometry and terrain in areas covered by Google Street View. 📢 To get started with Unity follow these steps: #AR #Google

This is pretty cool 👓 Google Announces Geospatial Creator powered by ARCore & Google Maps and it allows you to visualize, design, and publish world-anchored content by using Unity ! Few features available: 📌 Photorealistic 3D Tiles: Visualize the 3D geometry of the world and deploy location-anchored content accurately with high-resolution, photorealistic 3D tiles. 📌 Geospatial anchors: Place and anchor 3D content at any given latitude, longitude, and altitude with sub-meter accuracy in areas covered by Google Street View. 📌 Terrain anchors: Place and anchor 3D content with only latitude and longitude coordinates, using data from Google Maps to determine ground level. 📌 Rooftop anchors: Use rooftops to place and anchor 3D content with respect to the building geometry and terrain in areas covered by Google Street View. 📢 To get started with Unity follow these steps: #AR #Google

Dilmer

58,292 görüntüleme • 3 yıl önce

WOW. 😳 Apple just quietly won the 3D maps war at WWDC. Gaussian Splatting is coming to Apple Maps Flyover this fall. Apple Maps Flyover covers 300+ cities. Until yesterday, every single one was built on standard drone photogrammetry. The technology captures photos from the air and reconstructs 3D geometry from them. Gaussian Splatting does not reconstruct geometry. It represents the scene as millions of tiny 3D ellipsoids, each one carrying its own color and opacity information based on how light actually behaves in that location. The output is not a mesh model. It is a field of light. When you move through it, it does not crumble at the edges. The detail holds because it was never geometry to begin with. Apple has been hiring for this for years. Their SHARP model, published in research last year, generates photorealistic 3D scenes from a single image in under a second. Google has more sensor data than anyone. More Street View cars, more satellites, more capture history. On navigation accuracy and geodata depth, Google Maps is still ahead by most measures. But fidelity in 3D city rendering is a different competition, and Apple just set a bar in that. Most people will experience this in the fall without knowing the name of the technology. They will open Flyover, look at a city they know, and notice it looks different. Real, not rendered. That is the moment Gaussian Splatting stops being a research term and becomes something a billion people use. Bookmark this. It will look prescient by October.

WOW. 😳 Apple just quietly won the 3D maps war at WWDC. Gaussian Splatting is coming to Apple Maps Flyover this fall. Apple Maps Flyover covers 300+ cities. Until yesterday, every single one was built on standard drone photogrammetry. The technology captures photos from the air and reconstructs 3D geometry from them. Gaussian Splatting does not reconstruct geometry. It represents the scene as millions of tiny 3D ellipsoids, each one carrying its own color and opacity information based on how light actually behaves in that location. The output is not a mesh model. It is a field of light. When you move through it, it does not crumble at the edges. The detail holds because it was never geometry to begin with. Apple has been hiring for this for years. Their SHARP model, published in research last year, generates photorealistic 3D scenes from a single image in under a second. Google has more sensor data than anyone. More Street View cars, more satellites, more capture history. On navigation accuracy and geodata depth, Google Maps is still ahead by most measures. But fidelity in 3D city rendering is a different competition, and Apple just set a bar in that. Most people will experience this in the fall without knowing the name of the technology. They will open Flyover, look at a city they know, and notice it looks different. Real, not rendered. That is the moment Gaussian Splatting stops being a research term and becomes something a billion people use. Bookmark this. It will look prescient by October.

Shruti

19,832 görüntüleme • 1 ay önce

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.

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

49,239 görüntüleme • 1 ay önce

This AI paper just solved Google Earth's biggest problem. Satellites look down. Humans look across. That perspective gap is why 3D maps are limited to cities you can blanket with aerial flyovers. Skyfall-GS bridges the gap by synthesizing the views we never captured - rebuilding missing facades and street-level geometry using the world knowledge of diffusion models. And it does so with remarkable consistency. This is a taste of how we go from 3D maps in 3,000 cities to the entire planet. Watch my full video for the rundown:

This AI paper just solved Google Earth's biggest problem. Satellites look down. Humans look across. That perspective gap is why 3D maps are limited to cities you can blanket with aerial flyovers. Skyfall-GS bridges the gap by synthesizing the views we never captured - rebuilding missing facades and street-level geometry using the world knowledge of diffusion models. And it does so with remarkable consistency. This is a taste of how we go from 3D maps in 3,000 cities to the entire planet. Watch my full video for the rundown:

Bilawal Sidhu

135,003 görüntüleme • 8 ay önce

74 seconds to print a 3D Benchy! 🚢 Someone just printed a 3D Benchy in 74 seconds! For context: Benchy is the standard benchmark for 3D printing quality. Getting it done in 74 seconds required pushing every variable to its limit. Pulley and belt systems optimized for minimal slop, machine rigidity improvements to eliminate flex under high acceleration, input shaping to cancel out resonance frequencies that cause ringing artifacts at high speeds. A 3D scanner to analyze print quality objectively. Frequency analysis to identify and cancel specific resonance modes in the frame and motion system. Check it out here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

74 seconds to print a 3D Benchy! 🚢 Someone just printed a 3D Benchy in 74 seconds! For context: Benchy is the standard benchmark for 3D printing quality. Getting it done in 74 seconds required pushing every variable to its limit. Pulley and belt systems optimized for minimal slop, machine rigidity improvements to eliminate flex under high acceleration, input shaping to cancel out resonance frequencies that cause ringing artifacts at high speeds. A 3D scanner to analyze print quality objectively. Frequency analysis to identify and cancel specific resonance modes in the frame and motion system. Check it out here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

108,721 görüntüleme • 2 ay önce

Mapbox has a brand new 3D map style, still in beta! But it didn’t have a hackable live demo, so at Skydio we created one 😎 , try it out here: The updates include: - Hundreds of new 3D models for famous landmarks - New symbolic design that works hand in hand with the style - Day/night light shift built in! How does this help? Through more accurate 3D maps: - Data displayed on the map is more useful as it’s easier to understand where you are (our brains think in 3D) - More immersive 3D experiences are unlocked, not just navigation Looking forward to seeing where Mapbox takes this next

Alberto

43,942 görüntüleme • 2 yıl önce

3D capture is dope for media & entertainment, but the utilitarian applications might be even more impactful - literally x-ray vision making the unseen seen. With tools like Pix4D + RTK GPS (cm level accuracy) you can capture critical infrastructure, and overlay it at real-world locations in the future - allowing you to 'see' through concrete for future maintenance and construction.

3D capture is dope for media & entertainment, but the utilitarian applications might be even more impactful - literally x-ray vision making the unseen seen. With tools like Pix4D + RTK GPS (cm level accuracy) you can capture critical infrastructure, and overlay it at real-world locations in the future - allowing you to 'see' through concrete for future maintenance and construction.

Bilawal Sidhu

734,501 görüntüleme • 2 yıl önce

The game has really changed in animation. This is my latest project Kyōdai (きょうだい ) AKA → "Siblings." An AI film concept I'm developing Promise While not perfect by any means, tools like Seedance 2.0 allow for rapid prototyping and visual look development. Once explored, we bring in artists to hand draw and create the world to build and protect the IP. The VFX artist to build out the world with a hybrid 3D and AI methodology. This is the world we live in. What a time.

The game has really changed in animation. This is my latest project Kyōdai (きょうだい ) AKA → "Siblings." An AI film concept I'm developing Promise While not perfect by any means, tools like Seedance 2.0 allow for rapid prototyping and visual look development. Once explored, we bring in artists to hand draw and create the world to build and protect the IP. The VFX artist to build out the world with a hybrid 3D and AI methodology. This is the world we live in. What a time.

Dave Clark

15,858 görüntüleme • 3 ay önce