Video yükleniyor...

Video Yüklenemedi

Bu video yüklenirken bir sorun oluştu. Bu geçici bir ağ sorunundan kaynaklanıyor olabilir veya video kullanılamıyor olabilir.

Ana Sayfaya Dön

4DGS volumetric video captured with iPhones. 📱 Until now, capturing 4D Gaussian Splats meant million-dollar studios and fixed camera rigs. Radiant just changed the game - genlock-syncing multiple iPhone 17 Pro Max cameras with Tilta Chronos cage and Blackmagic ProDock into one fully wireless mobile capture rig. Pixel-level sync,... show more

Hugh Hou

3,890 subscribers

12,619 görüntüleme • 5 ay önce •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

12 Yorum

Infinite-Realities profil fotoğrafı

Infinite-Realities5 ay önce

>>> 4D Gaussian Splats meant million-dollar studios That iPhone setup "with all the accesories" is just as, if not more expensive than a professional grade machine vision setup. Not including the hidden processing fees that are subsidized by a 3rd party company that has investment

Hugh Hou profil fotoğrafı

Hugh Hou5 ay önce

@radiantimages It’s a different workflow. Yes maybe cheap is irrelevant - it’s getting easier as the tech moving forward that’s the key.

Infinite-Realities profil fotoğrafı

Infinite-Realities5 ay önce

@radiantimages That iPhone setup is not easier. How good was Apple or Blackmagic support..

tipatat profil fotoğrafı

tipatat5 ay önce

@AlexTench @radiantimages @gracia_vr solved the playback and streaming for 4DGS on XR and regular devices

Hugh Hou profil fotoğrafı

Hugh Hou5 ay önce

@AlexTench @radiantimages @gracia_vr Yes! I meant to follow up with you on that! Let’s work on @gracia_vr video together! Is there an API endpoint easy for us mortal to interface this?

Roman profil fotoğrafı

Roman5 ay önce

@radiantimages Is this your content? How much does the setup shown here cost?

Michael Mansouri profil fotoğrafı

Michael Mansouri5 ay önce

@radiantimages Amazing 🤩 thank you for creating such a great video and application

𝙀𝙙 𝘽𝙧𝙤𝙬𝙣 profil fotoğrafı

𝙀𝙙 𝘽𝙧𝙤𝙬𝙣5 ay önce

@radiantimages Those capture rigs are endodiegetic - point inwards to capture subjects, whereas I like the exodiegetic rigs (point outwards) to capture a whole environment

Hugh Hou profil fotoğrafı

Hugh Hou5 ay önce

@radiantimages That’s still way too expensive and clear up becomes impossible. Not sure G-Splat is the correct tech to even solve this.

fqqqR profil fotoğrafı

fqqqR5 ay önce

@radiantimages GLASSIAN SPLAT? GAUSSIAN BRAH

Loran profil fotoğrafı

Loran5 ay önce

@radiantimages impressive. with realistic personas or digital doubles AVP will become a wayback machine where everyone can teleport themselves in any place/time. Apple should help all those revolutionary initiatives

will yeh ᯅ/acc profil fotoğrafı

will yeh ᯅ/acc5 ay önce

@thereisnomouse @radiantimages “Wireless” “Mobile” — all I see are 20 iPhones wired together on mounting stands

Benzer Videolar

Volumetric Capture is Hard There is no magic solution. Anyone interested in spatial R&D can get access to some awesome datasets online to test with, which can be especially interesting when processed with 3DGS and played back as 4DGS. However you need a ton of compute power. (multiple 3080, 3090+, RTX5000+ etc) The Necessity of Multiple Cameras for Volumetric Capture Consider, for instance, this very useful fixed rig dataset comprising 20 camera streams provided by Facebook Research Or this datasets comprising 40 camera streams provided by Google The attached video demonstrates FB's RAW 3DGS data played back in real-time in our custom Sibr viewer. It's noticable how quickly the quality can breakdown out of the camera group frustrum. Even at this quality it takes a lot of time and energy to process and playback. It's not simple. Let alone the expertise required by the original research team who captured the data. Doing this with 20 cameras is hard. 150+ cameras even harder. Now imagine trying to achieve it with a single camera phone to playback on a Meta Quest or Spatial headset. #volumetriccaptureishard #camerasdontseearoundcorners #spatial

Volumetric Capture is Hard There is no magic solution. Anyone interested in spatial R&D can get access to some awesome datasets online to test with, which can be especially interesting when processed with 3DGS and played back as 4DGS. However you need a ton of compute power. (multiple 3080, 3090+, RTX5000+ etc) The Necessity of Multiple Cameras for Volumetric Capture Consider, for instance, this very useful fixed rig dataset comprising 20 camera streams provided by Facebook Research Or this datasets comprising 40 camera streams provided by Google The attached video demonstrates FB's RAW 3DGS data played back in real-time in our custom Sibr viewer. It's noticable how quickly the quality can breakdown out of the camera group frustrum. Even at this quality it takes a lot of time and energy to process and playback. It's not simple. Let alone the expertise required by the original research team who captured the data. Doing this with 20 cameras is hard. 150+ cameras even harder. Now imagine trying to achieve it with a single camera phone to playback on a Meta Quest or Spatial headset. #volumetriccaptureishard #camerasdontseearoundcorners #spatial

Infinite-Realities

129,521 görüntüleme • 3 yıl önce

Gaussian Splats are quickly becoming one of my favorite ways to move complex 3D assets between workflows. For this test I started with Panthera Spelaea, the Blender 5.2 splash artwork by Joanna Kobierska, available from under CC-BY. Using GPT-6 Astra, I had it build a 200-frame camera rig and send the renders directly to The Render Network through the API and export a COLMAP data set. NEXT: COLMAP → Postshot → Gaussian Splat. The result is a real-time, high-fidelity version of an insanely dense asset - millions of hairs and all - that I can now bring back into OTOY Octane, relight, reframe, drop into other scenes, or even publish straight to the web. Capture the visual complexity once, then carry it anywhere. Check out the splat:

Gaussian Splats are quickly becoming one of my favorite ways to move complex 3D assets between workflows. For this test I started with Panthera Spelaea, the Blender 5.2 splash artwork by Joanna Kobierska, available from under CC-BY. Using GPT-6 Astra, I had it build a 200-frame camera rig and send the renders directly to The Render Network through the API and export a COLMAP data set. NEXT: COLMAP → Postshot → Gaussian Splat. The result is a real-time, high-fidelity version of an insanely dense asset - millions of hairs and all - that I can now bring back into OTOY Octane, relight, reframe, drop into other scenes, or even publish straight to the web. Capture the visual complexity once, then carry it anywhere. Check out the splat:

Spenser Dickerson

11,721 görüntüleme • 27 gün önce

MVP of Multiview Video → Camera parameters + 3D keypoints. Visualized with Rerun The basic pipeline as of right now looks like this: 1. Capture 🔴 – Using 4 iPhones and an Insta360 Go. iPhone videos are captured via Final Cut Pro Multicam for easy sync and the exocentric view; the Insta360 Go is used for the egocentric view. 2. Sync 🕒 – Custom Gradio app using two Rerun viewers and callbacks for easily aligning frame timestamps so the ego and exo views are aligned. 3. Calibrate 🎯 – Use VGGT from Jianyuan and AI at Meta to get intrinsics/extrinsics for sparse cameras. 4. Estimate 3D 🕺 – Use RTMLib whole‑body keypoint estimator on each frame, then triangulate in 3D. What's missing? 1. No temporal coherence: I’m estimating keypoints one frame at a time and one camera at a time. This leads to a lot of jittering. For now, I plan on adding a One Euro Filter to help with jittering. Long term, I'd want to train a multiview keypoint estimator 2. Kinematic fitting is still missing; this is my next goal. The output will be joint angles, as explored in my previous posts. 3. Missing dense point cloud: VGGT seems to fail for me here. I’m looking to explore using MP‑SFM as a method for generating dense multiview depth maps + normals (plus it has a friendlier license compared to VGGT). 4. Eventually, creation of 4D Gaussian splatting using something akin to DN‑splatter—my long‑term goal is a data engine that provides poses/depths/splats/keypoints/etc.

MVP of Multiview Video → Camera parameters + 3D keypoints. Visualized with Rerun The basic pipeline as of right now looks like this: 1. Capture 🔴 – Using 4 iPhones and an Insta360 Go. iPhone videos are captured via Final Cut Pro Multicam for easy sync and the exocentric view; the Insta360 Go is used for the egocentric view. 2. Sync 🕒 – Custom Gradio app using two Rerun viewers and callbacks for easily aligning frame timestamps so the ego and exo views are aligned. 3. Calibrate 🎯 – Use VGGT from Jianyuan and AI at Meta to get intrinsics/extrinsics for sparse cameras. 4. Estimate 3D 🕺 – Use RTMLib whole‑body keypoint estimator on each frame, then triangulate in 3D. What's missing? 1. No temporal coherence: I’m estimating keypoints one frame at a time and one camera at a time. This leads to a lot of jittering. For now, I plan on adding a One Euro Filter to help with jittering. Long term, I'd want to train a multiview keypoint estimator 2. Kinematic fitting is still missing; this is my next goal. The output will be joint angles, as explored in my previous posts. 3. Missing dense point cloud: VGGT seems to fail for me here. I’m looking to explore using MP‑SFM as a method for generating dense multiview depth maps + normals (plus it has a friendlier license compared to VGGT). 4. Eventually, creation of 4D Gaussian splatting using something akin to DN‑splatter—my long‑term goal is a data engine that provides poses/depths/splats/keypoints/etc.

Pablo Vela

42,785 görüntüleme • 1 yıl önce

FreeTimeGS – Free Gaussian Primitives Anywhere, Anytime – has been making waves online over the past two days. You may have already seen it. If not, here’s a great example: a live demo with minimal cleanup and no heavy post-production. What’s remarkable is the simplicity of their setup. This example shows a basic semicircle rig made from smartphones and budget light stands. No complex volumetric or photogrammetry system required—and yet, the result plays smoothly right in a mobile browser. Yes, even on my iPhone. You can also view this on Vision Pro! The next logical step? Let’s bring this into the new Spatial Web standard IEEE IEEE 2874 and make it viewable in Apple Vision Pro, Android XR, and other upcoming headsets via open source XR web browser. Imagine freely flying through AI-powered Gaussian reconstructions directly in spatial environments cross platforms. We’re witnessing a major leap in spatial computing. AI-powered tools like this are reshaping every part of the creative pipeline. Can't wait to see what Apple has to say tomorrow at WWDC 25! Are you ready for it? What use cases excite you most? Drop your thoughts below—let’s discuss.

FreeTimeGS – Free Gaussian Primitives Anywhere, Anytime – has been making waves online over the past two days. You may have already seen it. If not, here’s a great example: a live demo with minimal cleanup and no heavy post-production. What’s remarkable is the simplicity of their setup. This example shows a basic semicircle rig made from smartphones and budget light stands. No complex volumetric or photogrammetry system required—and yet, the result plays smoothly right in a mobile browser. Yes, even on my iPhone. You can also view this on Vision Pro! The next logical step? Let’s bring this into the new Spatial Web standard IEEE IEEE 2874 and make it viewable in Apple Vision Pro, Android XR, and other upcoming headsets via open source XR web browser. Imagine freely flying through AI-powered Gaussian reconstructions directly in spatial environments cross platforms. We’re witnessing a major leap in spatial computing. AI-powered tools like this are reshaping every part of the creative pipeline. Can't wait to see what Apple has to say tomorrow at WWDC 25! Are you ready for it? What use cases excite you most? Drop your thoughts below—let’s discuss.

Hugh Hou

12,679 görüntüleme • 1 yıl önce

Fast Company just published a great piece on World Labs , Fei-Fei Li , Marble, and the idea that spatial intelligence / world models may be one of the next big shifts in AI. I was happy to be quoted in the article, but I also wanted to share more context about my own experience with World Labs and Marble, and why this direction is especially interesting to me. My starting point: volumetric capture — For the past few years I’ve been exploring and using volumetric capture and reconstruction (photogrammetry, NeRFs, 3D Gaussian Splats) mostly capturing locations around Montreal. Alleys, museums, urban interiors. I love every step of it: the capture itself, the pipeline, and what can be done with the output. Turning real spaces into real-time explorable systems. I do this personally, sharing explorations here, and professionally as chief technologist, and co-founder of Dpt. Physical reality + generative manipulation — In my work I’m especially drawn to mixing physical reality with generative and digital manipulation: using physical interfaces (light, clay, ink, ... ) to drive generative AI pipelines, building mixed reality prototypes that reshape your surroundings, or starting from real captured spaces and transforming them using tools like Marble. Like many people, I saw the World Labs announcement on Twitter in September 2024, and Marble when it surfaced in early December. But by then, I already had a sense something was coming. The first conversation — As someone deep into volumetric capture and radiance fields, I obviously knew about Ben Mildenhall and his pioneering work on NeRF. To my surprise, Ben reached out to me in late June 2024. He’d been following some of my experiments and wanted to chat about my process and workflows and how I was using this “stuff” creatively. At that point he didn’t share what he was building, but we had a genuinely great conversation about radiance fields, AI, and my work. He was curious about the creative perspective, not just the technical one. When the World Labs announcement dropped a few months later, it all made sense. I understood what Ben had been working on, and why the creative angle mattered to them. Then in August 2025, he invited me to try the Marble beta, and I’ve been experimenting with it since. Experimenting with Marble — The first thing I used Marble for was materializing scene and world concepts during ideation at the studio, and seeing if and how it could fit into our production pipeline. In parallel, I dove into a series of experiments focused on world manipulation: starting from real captured spaces and transforming them using Marble. I’d already been exploring that idea using img2img diffusion with ControlNet on NeRF renders, real-time video streams, and even mixed reality using headset camera feeds. But Marble brings something different. It generates persistent, spatially cohesive 3D worlds that can be rendered in real time across a wide range of devices. That’s a real shift. Experiment 01: Parallel Realities — The first experiment, Parallel Realities, starts from a volumetric capture of a real location, reconstructed as 3D Gaussian Splats. Using Marble, I generate an alternate version of that same space, something informed by the original architecture: abandoned, nature-reclaimed, alternate era. Then, using Spark (World Labs’ 3D Gaussian Splatting renderer for THREE.js) I make both realities coexist in the same spatial coordinate system. From there, I use a portal UX mechanic to let the user step between the real reconstruction and the Marble-generated version. Experiment 02: Hidden Depth The second experiment, Hidden Depth, does not transform a space as much as expand it. A captured location has a visual boundary (a mural, a doorway, a dark corridor) and Marble generates what exists beyond it. For example: a Montreal alley has a painted mural; step through it and you’re inside a world informed by what is actually depicted there. World Labs showcased part of this work here: And in their Spark 2.0 post: The project page is here: Why this matters to me — Being able to start from a real 3D Gaussian Splat scene and manipulate it with Marble opens up a lot of ideas. The 3DGS pipeline is becoming an increasingly compelling foundation for exploration, experimentation, and storytelling. What matters most to me right now is more control. The more I can steer the generated scene or world, the more useful the tool becomes. I want more features like the already existing multiple input images and Chisel, the blockout-based approach. I would like better local control, the ability to expand a generated world more and more while preserving coherence, and the ability to directly import 3D Gaussian Splat scenes to be used as a starting point. I want more ways to shape the result, not just a “prompt and hope” approach. — It is exciting to see this field moving from research and demos toward actual creative workflows.

Fast Company just published a great piece on World Labs , Fei-Fei Li , Marble, and the idea that spatial intelligence / world models may be one of the next big shifts in AI. I was happy to be quoted in the article, but I also wanted to share more context about my own experience with World Labs and Marble, and why this direction is especially interesting to me. My starting point: volumetric capture — For the past few years I’ve been exploring and using volumetric capture and reconstruction (photogrammetry, NeRFs, 3D Gaussian Splats) mostly capturing locations around Montreal. Alleys, museums, urban interiors. I love every step of it: the capture itself, the pipeline, and what can be done with the output. Turning real spaces into real-time explorable systems. I do this personally, sharing explorations here, and professionally as chief technologist, and co-founder of Dpt. Physical reality + generative manipulation — In my work I’m especially drawn to mixing physical reality with generative and digital manipulation: using physical interfaces (light, clay, ink, ... ) to drive generative AI pipelines, building mixed reality prototypes that reshape your surroundings, or starting from real captured spaces and transforming them using tools like Marble. Like many people, I saw the World Labs announcement on Twitter in September 2024, and Marble when it surfaced in early December. But by then, I already had a sense something was coming. The first conversation — As someone deep into volumetric capture and radiance fields, I obviously knew about Ben Mildenhall and his pioneering work on NeRF. To my surprise, Ben reached out to me in late June 2024. He’d been following some of my experiments and wanted to chat about my process and workflows and how I was using this “stuff” creatively. At that point he didn’t share what he was building, but we had a genuinely great conversation about radiance fields, AI, and my work. He was curious about the creative perspective, not just the technical one. When the World Labs announcement dropped a few months later, it all made sense. I understood what Ben had been working on, and why the creative angle mattered to them. Then in August 2025, he invited me to try the Marble beta, and I’ve been experimenting with it since. Experimenting with Marble — The first thing I used Marble for was materializing scene and world concepts during ideation at the studio, and seeing if and how it could fit into our production pipeline. In parallel, I dove into a series of experiments focused on world manipulation: starting from real captured spaces and transforming them using Marble. I’d already been exploring that idea using img2img diffusion with ControlNet on NeRF renders, real-time video streams, and even mixed reality using headset camera feeds. But Marble brings something different. It generates persistent, spatially cohesive 3D worlds that can be rendered in real time across a wide range of devices. That’s a real shift. Experiment 01: Parallel Realities — The first experiment, Parallel Realities, starts from a volumetric capture of a real location, reconstructed as 3D Gaussian Splats. Using Marble, I generate an alternate version of that same space, something informed by the original architecture: abandoned, nature-reclaimed, alternate era. Then, using Spark (World Labs’ 3D Gaussian Splatting renderer for THREE.js) I make both realities coexist in the same spatial coordinate system. From there, I use a portal UX mechanic to let the user step between the real reconstruction and the Marble-generated version. Experiment 02: Hidden Depth The second experiment, Hidden Depth, does not transform a space as much as expand it. A captured location has a visual boundary (a mural, a doorway, a dark corridor) and Marble generates what exists beyond it. For example: a Montreal alley has a painted mural; step through it and you’re inside a world informed by what is actually depicted there. World Labs showcased part of this work here: And in their Spark 2.0 post: The project page is here: Why this matters to me — Being able to start from a real 3D Gaussian Splat scene and manipulate it with Marble opens up a lot of ideas. The 3DGS pipeline is becoming an increasingly compelling foundation for exploration, experimentation, and storytelling. What matters most to me right now is more control. The more I can steer the generated scene or world, the more useful the tool becomes. I want more features like the already existing multiple input images and Chisel, the blockout-based approach. I would like better local control, the ability to expand a generated world more and more while preserving coherence, and the ability to directly import 3D Gaussian Splat scenes to be used as a starting point. I want more ways to shape the result, not just a “prompt and hope” approach. — It is exciting to see this field moving from research and demos toward actual creative workflows.

Hugues Bruyère

69,960 görüntüleme • 3 ay önce

$ETH (Weekly Time Frame) Ethereum has pulled back on the 4hr time frames into a bearish to neutral phase. But here is all the hopium you need today as we examine the weekly time frame. On days like today you just need to zoom out and cut the noise. So what does the weekly say about ETH 👇 The weekly time frame is in the beginning levels Phase 2 uptrend. We call it category or level 1. You tend to see another period of accumulation characterized by corrections. Not all but a lot of time I will color these accumulation zones turquoise. 👇 What we need is for Ethereum to slowly continue to either hold the Phase two level and slowly advance until all bear sell orders are absorbed. We will also keep a keen eye on the green Dots. If they stay we are good. If they end - I will diagnose it on the lower time frames in a video for everyone. For now we just stay patient and let the lower time frames work themselves out with this all the headline news. Those that want to be proactive should be managing their stop losses. Thats how you avoid feeling bad everytime this happens. Like any problem - it will always keep feeling worse until you attack the problem itself & stop avoiding it. Markets are the biggest teachers of this. Will keep everyone updated!

$ETH (Weekly Time Frame) Ethereum has pulled back on the 4hr time frames into a bearish to neutral phase. But here is all the hopium you need today as we examine the weekly time frame. On days like today you just need to zoom out and cut the noise. So what does the weekly say about ETH 👇 The weekly time frame is in the beginning levels Phase 2 uptrend. We call it category or level 1. You tend to see another period of accumulation characterized by corrections. Not all but a lot of time I will color these accumulation zones turquoise. 👇 What we need is for Ethereum to slowly continue to either hold the Phase two level and slowly advance until all bear sell orders are absorbed. We will also keep a keen eye on the green Dots. If they stay we are good. If they end - I will diagnose it on the lower time frames in a video for everyone. For now we just stay patient and let the lower time frames work themselves out with this all the headline news. Those that want to be proactive should be managing their stop losses. Thats how you avoid feeling bad everytime this happens. Like any problem - it will always keep feeling worse until you attack the problem itself & stop avoiding it. Markets are the biggest teachers of this. Will keep everyone updated!

Wick 🔥

22,243 görüntüleme • 8 gün önce

This is a big update! visionOS 2.4 Beta is now available and I’m genuinely excited! The public release hits in April, but here’s the rundown of what’s available in visionOS 2.4 Beta today: • Apple Intelligence is coming to Vision Pro! All those rumors that said the first model wouldn’t get it. Dead wrong. We’re getting Image Playground to whip up fun images, Genmoji for custom emojis, and my personal favorite, Writing Tools. This is just the start of Apple Intelligence on Vision Pro and I’m excited to see where it takes us. • Guest User feature! Hand your Vision Pro to someone, and your nearby iPhone or iPad pings with an 'Allow Guest User' option. You pick their apps from your device, kick off View Mirroring with AirPlay to see what they’re seeing, and guide them through the experience. It’s clean, easy, and something many of us have been asking for. • A new Spatial Gallery app! Apple’s curating a stunning lineup of spatial photos, videos, and panoramas from artists, filmmakers, and brands like Cirque du Soleil and Porsche. Can’t wait to dive into that. • A new Vision Pro app for iPhone! Browse and queue up apps or games to download, discover spatial content from Apple TV and Spatial Gallery, and grab handy tips—all from your iPhone. It’ll roll out with iOS 18.4 wherever Vision Pro’s sold. I think it’ll be super useful. visionOS 2.4 is a big step up and it’s another strong signal that we have a lot to look forward to with spatial computing from Apple. We are just getting started.

This is a big update! visionOS 2.4 Beta is now available and I’m genuinely excited! The public release hits in April, but here’s the rundown of what’s available in visionOS 2.4 Beta today: • Apple Intelligence is coming to Vision Pro! All those rumors that said the first model wouldn’t get it. Dead wrong. We’re getting Image Playground to whip up fun images, Genmoji for custom emojis, and my personal favorite, Writing Tools. This is just the start of Apple Intelligence on Vision Pro and I’m excited to see where it takes us. • Guest User feature! Hand your Vision Pro to someone, and your nearby iPhone or iPad pings with an 'Allow Guest User' option. You pick their apps from your device, kick off View Mirroring with AirPlay to see what they’re seeing, and guide them through the experience. It’s clean, easy, and something many of us have been asking for. • A new Spatial Gallery app! Apple’s curating a stunning lineup of spatial photos, videos, and panoramas from artists, filmmakers, and brands like Cirque du Soleil and Porsche. Can’t wait to dive into that. • A new Vision Pro app for iPhone! Browse and queue up apps or games to download, discover spatial content from Apple TV and Spatial Gallery, and grab handy tips—all from your iPhone. It’ll roll out with iOS 18.4 wherever Vision Pro’s sold. I think it’ll be super useful. visionOS 2.4 is a big step up and it’s another strong signal that we have a lot to look forward to with spatial computing from Apple. We are just getting started.

Justin Ryan ᯅ

83,414 görüntüleme • 1 yıl önce

Dormant Memories — a gallery regrouping my recent experiments built from real-world captures, reconstructed as 3D Gaussian Splats, and in many cases manipulated using World Labs' Marble. Everything is built with Spark, the 3D Gaussian splat renderer released by World Labs. It runs in the browser and can be experienced across devices: desktop, mobile, and headsets like Apple Vision Pro and Quest 3. This work comes out of something I've been exploring for a few years now: capturing fragments of the world (places, objects, moments...) and turning them into spaces that can then be revisited, manipulated, and explored in real time. What particularly interests me here is the process of creating alternate versions of the same place; starting from something that physically exists and using it as a base to explore variations, instead of generating from scratch. These explorations are part of what we do at Dpt.... same tools, same curiosity, same collaborative energy that shape the studio's work on interactive and immersive experiences. Some of these experiments were featured as part of the Spark 2.0 release by World Labs. Their technical blog post is a must-read; link in the thread ↓ These are experiments. They aren't fully optimized, they aren't bug-free, and the UX has rough edges. The goal is to explore, test, and learn. #GaussianSplatting #3DGS #pointcloud #WorldModels #sparkjs #threejs

Dormant Memories — a gallery regrouping my recent experiments built from real-world captures, reconstructed as 3D Gaussian Splats, and in many cases manipulated using World Labs' Marble. Everything is built with Spark, the 3D Gaussian splat renderer released by World Labs. It runs in the browser and can be experienced across devices: desktop, mobile, and headsets like Apple Vision Pro and Quest 3. This work comes out of something I've been exploring for a few years now: capturing fragments of the world (places, objects, moments...) and turning them into spaces that can then be revisited, manipulated, and explored in real time. What particularly interests me here is the process of creating alternate versions of the same place; starting from something that physically exists and using it as a base to explore variations, instead of generating from scratch. These explorations are part of what we do at Dpt.... same tools, same curiosity, same collaborative energy that shape the studio's work on interactive and immersive experiences. Some of these experiments were featured as part of the Spark 2.0 release by World Labs. Their technical blog post is a must-read; link in the thread ↓ These are experiments. They aren't fully optimized, they aren't bug-free, and the UX has rough edges. The goal is to explore, test, and learn. #GaussianSplatting #3DGS #pointcloud #WorldModels #sparkjs #threejs

Hugues Bruyère

12,728 görüntüleme • 5 ay önce

Luna is now VR-enabled! 🌐 We just ran a successful VR test with Luna on Apple Vision Pro We brought Luna into our office through VR, and it felt like she was right here! Soon fans will be able to step into her world, chat in real-time, and experience the magic of having Luna right there with you! 👓 While a full VR party will require further development, this milestone is a huge step toward bringing Luna closer to fans..Stay tuned as we unlock even more possibilities! Stay tuned for more updates! PS: Sorry for the slight shake in the video—it’s captured from my POV during the test! 😅 #LunaInVR

Luna is now VR-enabled! 🌐 We just ran a successful VR test with Luna on Apple Vision Pro We brought Luna into our office through VR, and it felt like she was right here! Soon fans will be able to step into her world, chat in real-time, and experience the magic of having Luna right there with you! 👓 While a full VR party will require further development, this milestone is a huge step toward bringing Luna closer to fans..Stay tuned as we unlock even more possibilities! Stay tuned for more updates! PS: Sorry for the slight shake in the video—it’s captured from my POV during the test! 😅 #LunaInVR

WhipQueen🐱🌙

28,288 görüntüleme • 1 yıl önce

One of the things I’m most excited about in our recently announced partnership with Niantic Spatial 🌎, is how clearly it shows what becomes possible when world-class reconstruction technology is paired with a new kind of imagery infrastructure. At a high level: Spexi drone pilots capture imagery, and Niantic Spatial turns it into incredible city-scale reconstructions. But the real unlock is the infrastructure behind that capture. At Spexi, we’ve built what we believe is the world’s first fully standardized drone imagery infrastructure called LayerDrone. Anyone with a compatible drone and the right credentials can contribute. No building flight plans. No estimating overlap. No adjusting camera settings in the field. Pilots simply get within visual line of sight of a Spexigon, open the Spexi app, press “Fly,” and the drone autonomously captures the 25-acre area to our standard. That standardization means imagery can be collected consistently, affordably, and repeatedly across cities, one Spexigon at a time (we have now captured over 225,000 of them). That is what makes living digital twins possible, dynamic representations of the physical world that can be updated as the world changes. Niantic Spatial’s city-scale Gaussian splats show what becomes possible when the right pixels go into the system. As physical AI advances, those pixels matter even more. Robots, drones, vehicles, maps, and spatial intelligence systems will all need current, high-resolution data about the real world. And as you can see below.. the results are not just beautiful, but real, measurable reconstructions of the physical world, one Spexigon at a time!

One of the things I’m most excited about in our recently announced partnership with Niantic Spatial 🌎, is how clearly it shows what becomes possible when world-class reconstruction technology is paired with a new kind of imagery infrastructure. At a high level: Spexi drone pilots capture imagery, and Niantic Spatial turns it into incredible city-scale reconstructions. But the real unlock is the infrastructure behind that capture. At Spexi, we’ve built what we believe is the world’s first fully standardized drone imagery infrastructure called LayerDrone. Anyone with a compatible drone and the right credentials can contribute. No building flight plans. No estimating overlap. No adjusting camera settings in the field. Pilots simply get within visual line of sight of a Spexigon, open the Spexi app, press “Fly,” and the drone autonomously captures the 25-acre area to our standard. That standardization means imagery can be collected consistently, affordably, and repeatedly across cities, one Spexigon at a time (we have now captured over 225,000 of them). That is what makes living digital twins possible, dynamic representations of the physical world that can be updated as the world changes. Niantic Spatial’s city-scale Gaussian splats show what becomes possible when the right pixels go into the system. As physical AI advances, those pixels matter even more. Robots, drones, vehicles, maps, and spatial intelligence systems will all need current, high-resolution data about the real world. And as you can see below.. the results are not just beautiful, but real, measurable reconstructions of the physical world, one Spexigon at a time!

Alec Wilson

10,695 görüntüleme • 3 ay önce

🚁 My war drone simulator Apocalypse Drone now has support for 32 players! I also made it Conquest/CTF so you have multiple bases that you have to capture, each round the map is procedurally generated and random so every time it's different (like Battlefield) There's still some bugs to work out and most importantly I have to figure out soldier animations, because they're fixed models now But I have got really far this time I think and coding with AI is really way further than it was a year ago, you mostly notice that how few times you get stuck, only one time this month building this I got stuck which was today where I moved the AI players to the server and they kept showing up as invisible, very buggy, every time I told it that it couldn't fix it though Then I asked it to fundamentally analyze the current server-side AI player code and make it work like industry standard, and it took a long time and fixed everything Last year I'd get stuck hundreds of times and the AI just couldn't get itself out of a hole, but now it can I think it's impressive that just last year only for the first time we could make actual games with AI But this year as non-game dev, I can get pretty close to the level of a multiplayer game from 20y ago (like Battlefield 1942, that lots of ideas here are based on, but with drones :D) Obviously we're still far away from AAA (I hate that term though) but the curve of exponential progress is there again, as it was in AI image generation, then video, and now code, first bad, then better, then good enough! Here's a video of gameplay from my drone sim You can play it with the link in the reply below and it's multiplayer!

🚁 My war drone simulator Apocalypse Drone now has support for 32 players! I also made it Conquest/CTF so you have multiple bases that you have to capture, each round the map is procedurally generated and random so every time it's different (like Battlefield) There's still some bugs to work out and most importantly I have to figure out soldier animations, because they're fixed models now But I have got really far this time I think and coding with AI is really way further than it was a year ago, you mostly notice that how few times you get stuck, only one time this month building this I got stuck which was today where I moved the AI players to the server and they kept showing up as invisible, very buggy, every time I told it that it couldn't fix it though Then I asked it to fundamentally analyze the current server-side AI player code and make it work like industry standard, and it took a long time and fixed everything Last year I'd get stuck hundreds of times and the AI just couldn't get itself out of a hole, but now it can I think it's impressive that just last year only for the first time we could make actual games with AI But this year as non-game dev, I can get pretty close to the level of a multiplayer game from 20y ago (like Battlefield 1942, that lots of ideas here are based on, but with drones :D) Obviously we're still far away from AAA (I hate that term though) but the curve of exponential progress is there again, as it was in AI image generation, then video, and now code, first bad, then better, then good enough! Here's a video of gameplay from my drone sim You can play it with the link in the reply below and it's multiplayer!

@levelsio

55,036 görüntüleme • 5 ay önce

Today I realized something absolutely with BitRobot Network You dont need to own a robot… to actually control one I was just sitting at my laptop and somehow I was moving a real robotic arm in real time At first I thought it would feel like a video game It didnt Theres a completely different feeling when you know this is happening in the real world not just on a screen Every movement matters. Every action generates data And then it hit me… This is how AI is learning to interact with the real world Not from code alone but from people like us Platforms like BitRobot are opening this to everyone No setup No cost No experience Just curiosity and the internet Someone sitting at home can now help train the next generation of robotics. The future isnt coming its happening right now. If you could control a robot right now what would you try first? 🤖👇

Today I realized something absolutely with BitRobot Network You dont need to own a robot… to actually control one I was just sitting at my laptop and somehow I was moving a real robotic arm in real time At first I thought it would feel like a video game It didnt Theres a completely different feeling when you know this is happening in the real world not just on a screen Every movement matters. Every action generates data And then it hit me… This is how AI is learning to interact with the real world Not from code alone but from people like us Platforms like BitRobot are opening this to everyone No setup No cost No experience Just curiosity and the internet Someone sitting at home can now help train the next generation of robotics. The future isnt coming its happening right now. If you could control a robot right now what would you try first? 🤖👇

RAJU

40,141 görüntüleme • 6 ay önce

📱 iPhone 17 Giveaway 📱 To celebrate our mobile app launching, we’re giving away an iPhone 17. backstory about the way we designed this Mobile app. For the last years, we’ve heard again and again that our users wanted folk to go Mobile. But it didn’t felt right to simply replicate the product and all its features on Mobile. Desktop and Mobile are completely different contexts. Our desktop version is built for productivity. We designed the interface to be simple and lightweight so not to overwhelm you, but with condensed information so you can have a high level view of what’s going on in your CRM. We’ve built it for bulk actions so can get through your tasks in reduced time. It’s the perfect companion for deep, focused work. Mobile is different. You check your mobile when you’re on the go. Heading into the office, between client meetings, traveling for work, or simply off and far from your screens. And salespeople are often far from their desktop. Sales is about connecting, go meet your prospects on the fields, engage with them, shake hands. These moments are precious, that’s where trust is built. To shine during these moments, it’s about the little things. Remembering your prospect’ daughter’ name. Making sure action points discussed in the meeting are well passed to the team. Ensuring you actually reach out to the lead you met at that conference, as you promised. We wanted to design the perfect companion for that. Contacts by folk is built as a contacts app that shows all your contacts from folk CRM. But designed to give you context and let you capture more context. - Sync contacts from multiple places - your emails, LinkedIn, calendar, WhatsApp, or any contact you add in the CRM - Add new contacts easily, including with business card scanning - Search contacts smartly - you can search by name, but also company, job title or even through your notes - Add notes on the go, mention your teammates, and even record notes with voice-to-text - View past notes and past interactions before a meeting across all your channels Think the native Contacts app, reinvented for today. Want to win? Comment “CONTACTS” below 👇👇👇 We’ll randomly pick 1 winner ◾ 1x iPhone 17 ◾ 1 year of folk CRM ⚠️ Get a second entry if you repost!

📱 iPhone 17 Giveaway 📱 To celebrate our mobile app launching, we’re giving away an iPhone 17. backstory about the way we designed this Mobile app. For the last years, we’ve heard again and again that our users wanted folk to go Mobile. But it didn’t felt right to simply replicate the product and all its features on Mobile. Desktop and Mobile are completely different contexts. Our desktop version is built for productivity. We designed the interface to be simple and lightweight so not to overwhelm you, but with condensed information so you can have a high level view of what’s going on in your CRM. We’ve built it for bulk actions so can get through your tasks in reduced time. It’s the perfect companion for deep, focused work. Mobile is different. You check your mobile when you’re on the go. Heading into the office, between client meetings, traveling for work, or simply off and far from your screens. And salespeople are often far from their desktop. Sales is about connecting, go meet your prospects on the fields, engage with them, shake hands. These moments are precious, that’s where trust is built. To shine during these moments, it’s about the little things. Remembering your prospect’ daughter’ name. Making sure action points discussed in the meeting are well passed to the team. Ensuring you actually reach out to the lead you met at that conference, as you promised. We wanted to design the perfect companion for that. Contacts by folk is built as a contacts app that shows all your contacts from folk CRM. But designed to give you context and let you capture more context. - Sync contacts from multiple places - your emails, LinkedIn, calendar, WhatsApp, or any contact you add in the CRM - Add new contacts easily, including with business card scanning - Search contacts smartly - you can search by name, but also company, job title or even through your notes - Add notes on the go, mention your teammates, and even record notes with voice-to-text - View past notes and past interactions before a meeting across all your channels Think the native Contacts app, reinvented for today. Want to win? Comment “CONTACTS” below 👇👇👇 We’ll randomly pick 1 winner ◾ 1x iPhone 17 ◾ 1 year of folk CRM ⚠️ Get a second entry if you repost!

Simo Lemhandez

51,921 görüntüleme • 2 ay önce

Day 18. Building the game I've dreamed of for 15 years with AI. I've learned how to build proper levels with AI. I take the design and the architecture, and AI helps me put it all together and check the balance. I made the first level of my game almost entirely by hand. I wanted to understand how it works and what I like, from how big the trees should be to how the textures tile. After a day digging around in the terrain tools it all made sense, and I could see how much of it could be automated by painting zones. Claude helped me a lot with the tileable textures. Matching the colors took a ton of iterations, and that was the hardest part of the whole level. For level two I took a different route. I built myself a simple HTML planner with a logical map of the level, where I place everything and design the layout. Painting a level and making it fun to play are two different jobs, so I kept the design for myself. We even made automated tests with Claude: 2D simulations that show which routes a player takes and how hard the level is. They're rough, but they give a real sense of how the level plays. Once the plan was ready, I handed everything to Claude, and 3-4 hours later I had a working level. It reused the patterns from my first level, scattered objects unevenly so nothing looks placed on a grid, and generated extra props whenever I asked. I showed it one example, it picked up what worked, and we turned that into a skill for the next levels. The video is a quick flight over level two, then how it got there, from my first sketch to the version I play now.

Day 18. Building the game I've dreamed of for 15 years with AI. I've learned how to build proper levels with AI. I take the design and the architecture, and AI helps me put it all together and check the balance. I made the first level of my game almost entirely by hand. I wanted to understand how it works and what I like, from how big the trees should be to how the textures tile. After a day digging around in the terrain tools it all made sense, and I could see how much of it could be automated by painting zones. Claude helped me a lot with the tileable textures. Matching the colors took a ton of iterations, and that was the hardest part of the whole level. For level two I took a different route. I built myself a simple HTML planner with a logical map of the level, where I place everything and design the layout. Painting a level and making it fun to play are two different jobs, so I kept the design for myself. We even made automated tests with Claude: 2D simulations that show which routes a player takes and how hard the level is. They're rough, but they give a real sense of how the level plays. Once the plan was ready, I handed everything to Claude, and 3-4 hours later I had a working level. It reused the patterns from my first level, scattered objects unevenly so nothing looks placed on a grid, and generated extra props whenever I asked. I showed it one example, it picked up what worked, and we turned that into a skill for the next levels. The video is a quick flight over level two, then how it got there, from my first sketch to the version I play now.

Stefan 3D AI

43,759 görüntüleme • 4 gün önce

This soldiering training is the most impressive and immersive I've ever tried. It is 10x better than a YouTube tutorial video. It really allowed me to see the procedure from all the points of view, and even get super close to get the details. It is a collaboration between @gracia_vr and Imperial College London: they recorded a soldering session with Gaussian Splatting Videos (4DGS), so that you can enjoy it from your VR headset. You can see the action happening in front of you; you can pause and re-watch what you need, change the point of view, get closer, get more distant. And the quality with which it has been shot is impressive: I enjoyed this experience with my DELL Pro Max Tower T2 with NVIDIA Pro RTX 6000, and I could really see all the small details of the PCB that was being soldered! I was really impressed by it. But I also noticed some drawbacks. First of all, some scenes have artifacts that make seeing the details of the PCB hard. I think when it comes to training involving small details, the capture and reproduction of the splat should be flawless. Then, as much as I loved it as a passive experience, I would have liked to have also some sort of practice session in VR. The power of VR is to let you learn by doing in full safety, and this kind of training does not exploit it. But maybe the best way to enjoy it would be in MR, where you have this training video close to a real workbench where you do the actual soldering while following the tutorial. Gaussian Splat can really revolutionize training: this kind of recording is much better than any flatscreen experience, and more accurate than any 3D CGI recostruction. I suggest you give it a go at this experience in the Gracia app (it's free). Then let me know your impressions! #VirtualReality #training #DellProPrecision #GaussianSplat #technology [Disclaimer: I'm a DELL Pro Precision Ambassador, and this is why I mentioned the model of my PC. I have been given a PC to do cool tests and share my results on social media. No monetary compensation or sales affiliation is part of the collaboration]

This soldiering training is the most impressive and immersive I've ever tried. It is 10x better than a YouTube tutorial video. It really allowed me to see the procedure from all the points of view, and even get super close to get the details. It is a collaboration between @gracia_vr and Imperial College London: they recorded a soldering session with Gaussian Splatting Videos (4DGS), so that you can enjoy it from your VR headset. You can see the action happening in front of you; you can pause and re-watch what you need, change the point of view, get closer, get more distant. And the quality with which it has been shot is impressive: I enjoyed this experience with my DELL Pro Max Tower T2 with NVIDIA Pro RTX 6000, and I could really see all the small details of the PCB that was being soldered! I was really impressed by it. But I also noticed some drawbacks. First of all, some scenes have artifacts that make seeing the details of the PCB hard. I think when it comes to training involving small details, the capture and reproduction of the splat should be flawless. Then, as much as I loved it as a passive experience, I would have liked to have also some sort of practice session in VR. The power of VR is to let you learn by doing in full safety, and this kind of training does not exploit it. But maybe the best way to enjoy it would be in MR, where you have this training video close to a real workbench where you do the actual soldering while following the tutorial. Gaussian Splat can really revolutionize training: this kind of recording is much better than any flatscreen experience, and more accurate than any 3D CGI recostruction. I suggest you give it a go at this experience in the Gracia app (it's free). Then let me know your impressions! #VirtualReality #training #DellProPrecision #GaussianSplat #technology [Disclaimer: I'm a DELL Pro Precision Ambassador, and this is why I mentioned the model of my PC. I have been given a PC to do cool tests and share my results on social media. No monetary compensation or sales affiliation is part of the collaboration]

TonyVT SkarredGhost

38,511 görüntüleme • 1 ay önce