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Right now, 4D capture mostly belongs to labs, studios, and expensive multi-camera rigs. Our goal at KIRI has always been different: put spatial capture in the hands of regular people, on the device they already carry with them. This is a work in progress, but it’s a huge step... show more

KIRI Engine - 3D Scanner App

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13,429 Aufrufe • vor 3 Monaten •via X (Twitter)

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This is some quietly impressive work on making video world models actually controllable in 4D space. VerseCrafter lets you take an input image, use something like Blender to animate the 3D camera path and object trajectories, then uses that to condition generation. Scribbling in 2D feels so crude in comparison. The authors represent everything in a shared 4D world state - static background as a point cloud, moving objects as 3D gaussian trajectories. The gaussians are an interesting choice because they capture position, shape, and orientation probabilistically rather than forcing rigid bounding boxes or category specific models like SMPL-X for human bodies. They bolt this onto frozen Wan2.1 with a lightweight adapter, so they get a strong video prior. They also built a pipeline to auto extract 4D annotations from real world videos to train this puppy. It doesn't look sexy yet, but IMO this is the interface video world models need - actual 3D authoring tools to exert control rather than crude scribbles and prompt incantations.

This is some quietly impressive work on making video world models actually controllable in 4D space. VerseCrafter lets you take an input image, use something like Blender to animate the 3D camera path and object trajectories, then uses that to condition generation. Scribbling in 2D feels so crude in comparison. The authors represent everything in a shared 4D world state - static background as a point cloud, moving objects as 3D gaussian trajectories. The gaussians are an interesting choice because they capture position, shape, and orientation probabilistically rather than forcing rigid bounding boxes or category specific models like SMPL-X for human bodies. They bolt this onto frozen Wan2.1 with a lightweight adapter, so they get a strong video prior. They also built a pipeline to auto extract 4D annotations from real world videos to train this puppy. It doesn't look sexy yet, but IMO this is the interface video world models need - actual 3D authoring tools to exert control rather than crude scribbles and prompt incantations.

Bilawal Sidhu

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Kling 2.6 Motion Capture is so good. It's a huge leap forward. We've been able to do motion capture with AI for a while, but the quality bump finally made this approach useful. Here are the steps: - Get a reference video - record it or get a stock video - Grab the start frame of that video - Edit it using Nano Banana Pro. Ask to replace character and background. - Select the Kling 2.6 Motion Capture model in the video generator on Freepik (now Magnific) - Upload reference video + set the edited start frame - Video prompt can be simple e.g. "Gandalf dancing"

Kling 2.6 Motion Capture is so good. It's a huge leap forward. We've been able to do motion capture with AI for a while, but the quality bump finally made this approach useful. Here are the steps: - Get a reference video - record it or get a stock video - Grab the start frame of that video - Edit it using Nano Banana Pro. Ask to replace character and background. - Select the Kling 2.6 Motion Capture model in the video generator on Freepik (now Magnific) - Upload reference video + set the edited start frame - Video prompt can be simple e.g. "Gandalf dancing"

Martin LeBlanc

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2 WOMEN. 1 GROCERY STORE. AND THE CAMERA CATCHES A MOMENT THAT LOOKS TOO PERFECTLY CASUAL. They are standing in the middle of a store aisle like this is completely normal. One is talking. The other turns toward the camera. Then the interaction changes. > The fluorescent lights stay flat and ordinary. > The shelves stay packed behind them. > Their movements stay casual instead of looking choreographed. > Even the background feels more important because nobody is paying attention to the camera. That is why the clip feels different from a normal staged shoot. It looks like someone just happened to press record. And those are usually the clips people watch twice...

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Asher Crowe 🪺

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Asmongold gathered his guild members in “Olympus” to announce their huge progress, revealing that the guild has surpassed 10K members in World of Warcraft: Forever Beta 😳👀 “Now, guys, we’ve made a huge amount of progress and a massive, insane amount of progress right now with Olympus. We’ve put in an insane amount of work. I think that at this point, gentlemen, have we reached over 10,000 members in Olympus”

Asmongold gathered his guild members in “Olympus” to announce their huge progress, revealing that the guild has surpassed 10K members in World of Warcraft: Forever Beta 😳👀 “Now, guys, we’ve made a huge amount of progress and a massive, insane amount of progress right now with Olympus. We’ve put in an insane amount of work. I think that at this point, gentlemen, have we reached over 10,000 members in Olympus”

Prism

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Yeaah with Kartel.ai and Jesse Wellens ! So training Lora for character on Flux and also for Wan 2.1 14B ( using dataset video ) make a Huge difference. So here you are seeing a volumetric capture of Jesse Wellens that we did in at the spatial studio of Kartel.ai We use a a World Labs gaussian splatting to create a simple environment that we put with the volumetric capture in our own webgl viewer ( out soon for everyone ). After that, We use after this output in a ComfyUI workflow with Wan Fun control ( a bit similar Vace but its working for Wan 14B) with the double loras , the first to generate the first frame with flux, and the second one to guide the generation of Wan 2.1 Control. So we keep very good consistency of character and position, and creating amazing worlds :) ! Hope you will find it cool !

Yeaah with Kartel.ai and Jesse Wellens ! So training Lora for character on Flux and also for Wan 2.1 14B ( using dataset video ) make a Huge difference. So here you are seeing a volumetric capture of Jesse Wellens that we did in at the spatial studio of Kartel.ai We use a a World Labs gaussian splatting to create a simple environment that we put with the volumetric capture in our own webgl viewer ( out soon for everyone ). After that, We use after this output in a ComfyUI workflow with Wan Fun control ( a bit similar Vace but its working for Wan 14B) with the double loras , the first to generate the first frame with flux, and the second one to guide the generation of Wan 2.1 Control. So we keep very good consistency of character and position, and creating amazing worlds :) ! Hope you will find it cool !

Lovis Odin

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Sneak peek from the lab. Work in progress of the real-time face tracking, via iPhone, Clone v2 cinematic rig. Simple viewport capture, no lighting or shading. Effective expression capture is key for conveying emotions accurately with your Clones. Our new cinematic rig has been constructed with flexibility in mind. We've carefully refined the 52 blend shapes that drive the facial expressions, and the face controls themselves, to achieve a more natural look. We have more iteration cycles to go through before we hit our target but you can already see a great difference from v1. This upgrade opens up a world of possibilities, from high-fidelity dynamic VRMs adaptable to various platforms to virtual production capabilities and V-Tubing with improved face filters. Our goal is simple: To help eliminate technical barriers and provide a more seamless and inclusive utility for all of our community, all while ensuring quality remains at the core of everything we do.

Sneak peek from the lab. Work in progress of the real-time face tracking, via iPhone, Clone v2 cinematic rig. Simple viewport capture, no lighting or shading. Effective expression capture is key for conveying emotions accurately with your Clones. Our new cinematic rig has been constructed with flexibility in mind. We've carefully refined the 52 blend shapes that drive the facial expressions, and the face controls themselves, to achieve a more natural look. We have more iteration cycles to go through before we hit our target but you can already see a great difference from v1. This upgrade opens up a world of possibilities, from high-fidelity dynamic VRMs adaptable to various platforms to virtual production capabilities and V-Tubing with improved face filters. Our goal is simple: To help eliminate technical barriers and provide a more seamless and inclusive utility for all of our community, all while ensuring quality remains at the core of everything we do.

Jarlan Perez

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So many wins to celebrate today! Jarren and Kolette having a show together in Gensan is already a huge win. Seeing them happy and carefree together? Another win. But the ultimate highlight has to be them performing the Jarlette dance, it’s the best win of all! Let’s not forget, the Jarlette dance was Moonstrings’ special gift to them. It’s the dance step they created together, which blew up on TikTok thanks to Moonstrings’ efforts. We’ve been waiting months to see them perform this, and today, we finally got to witness them perform it on stage, right in front of so many Moonstrings. Today truly belongs to Jarlette and Moonstrings, a celebration of hard work, love, and shared joy. What an unforgettable day! KOLETTE MEMErriest XMAS JARLETTE GENSHINES TOGETHER

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One Last Tow Before the Scrap Yard ✈️ A retired New Pacific 757-200 is making its final journey , not to another airport, but toward the scrapyard at Mojave Air & Space Port. Once built to cross oceans and carry hundreds of passengers, this 757 is now being towed toward the end of its story. From takeoff rolls to its final tow… every aircraft eventually has a last flight. Would you rather see retired airliners preserved in museums, or is recycling them the right way to give the aircraft a second life? 👇 With sdf.planespotting

aircraftmaintenancengineer

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Interesting development - I was told numerous stories about what happened yesterday at Crosby. One being it was a group of Asian men attacking teenage girls. Some as young as 14. I dismissed it as rumours and told people to watch out for racism. People unfairly targeting Asians and making lies up about them. But I’ve just been sent this. Now unless there is a conspiracy to frame them. It’s now looking like this is the case. The only other possibility is that this was 2 separate incidents. But either way we can’t live in peace with savages who do this on a public beach in front of families. I don’t want to speculate. So I’m going to bite my tongue on this for the time being in case I’m wrong. It has since been confirmed that teenage girls have been attacked with a bladed item. But the attacker has not been confirmed. I’m currently speaking to the Echo to work out what’s going on.

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A driver caught on surveillance camera flying through an intersection in Murray Utah and the internet is going crazy trying to figure out who is at fault here - this is exactly the kind of reckless driving that turns a normal afternoon into a tragedy in a split second. Intersections are already one of the most dangerous spots on any road and when somebody decides the rules don’t apply to them everybody around them becomes a victim of that decision. Watch the video and drop your verdict in the comments.

A driver caught on surveillance camera flying through an intersection in Murray Utah and the internet is going crazy trying to figure out who is at fault here - this is exactly the kind of reckless driving that turns a normal afternoon into a tragedy in a split second. Intersections are already one of the most dangerous spots on any road and when somebody decides the rules don’t apply to them everybody around them becomes a victim of that decision. Watch the video and drop your verdict in the comments.

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The situation in the Middle East right now is serious, and many people in the region are going through uncertain times. Dubai and the entire Gulf region have always been incredibly important for our films and for our boss. Millions of Indians live and work there, and a massive fan base of Rocking Star stands proudly in that region. For a film of this scale, the experience is meant to be shared together by fans across the world at the same time. When such a large section of our audience is facing tension and uncertainty, it only makes sense to wait for the right moment so everyone can celebrate the film together in theatres. This decision shows responsibility and respect for fans everywhere. Cinema is about bringing people together, and the goal is for every fan, whether in India, Dubai, or anywhere in the world, to enjoy the experience without worry. Real fans understand this. The celebration will be bigger when the time is right. 🔥

The situation in the Middle East right now is serious, and many people in the region are going through uncertain times. Dubai and the entire Gulf region have always been incredibly important for our films and for our boss. Millions of Indians live and work there, and a massive fan base of Rocking Star stands proudly in that region. For a film of this scale, the experience is meant to be shared together by fans across the world at the same time. When such a large section of our audience is facing tension and uncertainty, it only makes sense to wait for the right moment so everyone can celebrate the film together in theatres. This decision shows responsibility and respect for fans everywhere. Cinema is about bringing people together, and the goal is for every fan, whether in India, Dubai, or anywhere in the world, to enjoy the experience without worry. Real fans understand this. The celebration will be bigger when the time is right. 🔥

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In the summer of 2023, I cold emailed Jensen Huang and asked to capture a NeRF of him at SIGGRAPH. He responded in about an hour and said yes. A radiance field is, in the simplest terms, akin to a 3D photograph. A moment in time, so completely reconstructed that you can move through it and see it from angles the original cameras never occupied. NeRFs were the original method. Gaussian splatting, which debuted at that same SIGGRAPH, has since become the dominant form of radiance field. I called my late friend James, who told me we needed to begin practicing immediately. We ran capture after capture for weeks until we consistently got the capture time down to ~30 seconds with one camera. Later, in a hallway at the LA Convention Center during SIGGRAPH, I captured the portrait you're seeing now, a full 360° gaussian splat of Jensen, rendered here as a 2D flythrough. Afterward, I continued the conversation with him and members of his team to make the case for radiance fields as a foundational representation for imaging. To my surprise, they listened. Three years later, NVIDIA has several works, including NuRec, fVDB, 3DGRUT, and gsplat all utilizing radiance fields. The landscape has evolved enough that the reasoning is obvious. Gaussian splatting has begun to ship across some of the world’s largest industries, including autonomous vehicles, AEC, geospatial, media and entertainment, robotics, e-commerce, hospitality. It’s become clear that lifelike 3D is here to stay. And yet I think we will look back and be disappointed by how late we started taking 3D portraits of the people around us, just like how we have sparse 2D photos of our grandparents and great grandparents. We have billions of photographs of the people we know and love, but almost no radiance fields of them. I'll be returning to SIGGRAPH in LA where this was initially captured three years ago, with the landscape looking significantly different. Radiance fields are more under deployed than ever relative to what they can do. I'm excited for the future of imaging, and for 2D to transition into 3D. I have a few things up my sleeve that I think will make that case plainly.

In the summer of 2023, I cold emailed Jensen Huang and asked to capture a NeRF of him at SIGGRAPH. He responded in about an hour and said yes. A radiance field is, in the simplest terms, akin to a 3D photograph. A moment in time, so completely reconstructed that you can move through it and see it from angles the original cameras never occupied. NeRFs were the original method. Gaussian splatting, which debuted at that same SIGGRAPH, has since become the dominant form of radiance field. I called my late friend James, who told me we needed to begin practicing immediately. We ran capture after capture for weeks until we consistently got the capture time down to ~30 seconds with one camera. Later, in a hallway at the LA Convention Center during SIGGRAPH, I captured the portrait you're seeing now, a full 360° gaussian splat of Jensen, rendered here as a 2D flythrough. Afterward, I continued the conversation with him and members of his team to make the case for radiance fields as a foundational representation for imaging. To my surprise, they listened. Three years later, NVIDIA has several works, including NuRec, fVDB, 3DGRUT, and gsplat all utilizing radiance fields. The landscape has evolved enough that the reasoning is obvious. Gaussian splatting has begun to ship across some of the world’s largest industries, including autonomous vehicles, AEC, geospatial, media and entertainment, robotics, e-commerce, hospitality. It’s become clear that lifelike 3D is here to stay. And yet I think we will look back and be disappointed by how late we started taking 3D portraits of the people around us, just like how we have sparse 2D photos of our grandparents and great grandparents. We have billions of photographs of the people we know and love, but almost no radiance fields of them. I'll be returning to SIGGRAPH in LA where this was initially captured three years ago, with the landscape looking significantly different. Radiance fields are more under deployed than ever relative to what they can do. I'm excited for the future of imaging, and for 2D to transition into 3D. I have a few things up my sleeve that I think will make that case plainly.

Radiance Fields

18,084 Aufrufe • vor 3 Monaten

One of the followers sent this video in of him giving it to the Commi’s in Bootle. There is a known theory that the reason we have all this is because of Russia/Qatar/Iran are spending billions on bot accounts pushing all this on the internet. They also fund activists to push this on our streets and university campuses. Knowing the divide and damage it causes to society. They also push Palestine protests which is why everyone is up in arms about Palestine but no other genocides happening right now. Not a peep out of them. The people who stand at hotels with refugees welcome signs. Most of them are paid to do so. They are literally carrying out the dirty work for countries that want to bring us down. And they have the cheek to call normal everyday people who just want to live in peace the “divisive” ones. We will never live in a peaceful society while these people exist. Even if we do free Palestine. They will just move onto something else to divide our society. For them the revolution never ends.

One of the followers sent this video in of him giving it to the Commi’s in Bootle. There is a known theory that the reason we have all this is because of Russia/Qatar/Iran are spending billions on bot accounts pushing all this on the internet. They also fund activists to push this on our streets and university campuses. Knowing the divide and damage it causes to society. They also push Palestine protests which is why everyone is up in arms about Palestine but no other genocides happening right now. Not a peep out of them. The people who stand at hotels with refugees welcome signs. Most of them are paid to do so. They are literally carrying out the dirty work for countries that want to bring us down. And they have the cheek to call normal everyday people who just want to live in peace the “divisive” ones. We will never live in a peaceful society while these people exist. Even if we do free Palestine. They will just move onto something else to divide our society. For them the revolution never ends.

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Trained on zero real-world data. Learned to walk, pick up boxes, and follow multi-step instructions... in the REAL world. ( 📌 Paper below) Researchers from Amazon FAR, Berkeley, Stanford, and CMU scanned real rooms with an iPhone, rebuilt them as 3D Gaussian Splatting scenes, then generated 48,000 synthetic trajectories of a Unitree G1 walking, grasping, and placing objects inside those virtual replicas. They rendered the robot's first-person camera view from each run and paired it with the matching language instruction and motion data. That's the dataset every humanoid team needs and nobody has: synced egocentric video + language + kinematics, at scale. Instead of collecting it in the real world, they manufactured it. They trained a vision-language-kinematics policy on that synthetic data alone, then deployed it on the physical G1 across five task types: navigation to a named object, lifting boxes of three different sizes with no per-size tuning, chained multi-step tasks, robustness to mid-task layout changes and flickering lights, and multi-minute long-horizon runs. No real-world fine-tuning at any point. Real-world interaction data has been the hard limit on humanoid learning... slow, expensive, and small. If scanning a room once and synthesizing thousands of labeled interactions holds up as a general recipe, that limit moves. Data stops being the bottleneck robotics teams have to solve for. 📌 Paper: Project: ——- Weekly robotics and AI insights. Subscribe free:

Trained on zero real-world data. Learned to walk, pick up boxes, and follow multi-step instructions... in the REAL world. ( 📌 Paper below) Researchers from Amazon FAR, Berkeley, Stanford, and CMU scanned real rooms with an iPhone, rebuilt them as 3D Gaussian Splatting scenes, then generated 48,000 synthetic trajectories of a Unitree G1 walking, grasping, and placing objects inside those virtual replicas. They rendered the robot's first-person camera view from each run and paired it with the matching language instruction and motion data. That's the dataset every humanoid team needs and nobody has: synced egocentric video + language + kinematics, at scale. Instead of collecting it in the real world, they manufactured it. They trained a vision-language-kinematics policy on that synthetic data alone, then deployed it on the physical G1 across five task types: navigation to a named object, lifting boxes of three different sizes with no per-size tuning, chained multi-step tasks, robustness to mid-task layout changes and flickering lights, and multi-minute long-horizon runs. No real-world fine-tuning at any point. Real-world interaction data has been the hard limit on humanoid learning... slow, expensive, and small. If scanning a room once and synthesizing thousands of labeled interactions holds up as a general recipe, that limit moves. Data stops being the bottleneck robotics teams have to solve for. 📌 Paper: Project: ——- Weekly robotics and AI insights. Subscribe free:

Ilir Aliu

12,950 Aufrufe • vor 2 Monaten