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3D scans usually begin as triangle meshes, which are great for capturing, viewing, and sharing real-world objects. For editing, animation, cleanup, or production workflows, quad-based topology can be much easier to work with. Our Quad-Mesh Retopology helps convert scan meshes into clean quad meshes, making your model easier to... show more

KIRI Engine - 3D Scanner App

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11,048 次观看 • 2 个月前 •via X (Twitter)

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With Hunyuan3D World Model 1.0 now released and open-sourced, we're excited to showcase the technical highlights behind this impressive innovation: ✅360° Panoramic Generation: Creates complete, immersive “world scenes”, far beyond localized views. ✅Explorable 3D Scene Generation: Generates diverse, spatially consistent 3D worlds from text/image for truly immersive exploration. ✅Interactive/Editable: Achieves separation of foreground objects, background terrain, ground, and sky, for seamless secondary editing. ✅Exportable Mesh: Generated scenes can be exported as 3D meshes for direct import into mainstream game engines and modeling software. ✅Industry-Leading SOTA Evaluation: Surpasses state-of-the-art open-source models in generation quality. As the industry's first open-source model for physical simulation and explorable world generation, Hunyuan3D World Model 1.0 aims to foster a collaborative community ecosystem with developers and enthusiasts. ✨ Try it now: 🤗 Hugging Face:

With Hunyuan3D World Model 1.0 now released and open-sourced, we're excited to showcase the technical highlights behind this impressive innovation: ✅360° Panoramic Generation: Creates complete, immersive “world scenes”, far beyond localized views. ✅Explorable 3D Scene Generation: Generates diverse, spatially consistent 3D worlds from text/image for truly immersive exploration. ✅Interactive/Editable: Achieves separation of foreground objects, background terrain, ground, and sky, for seamless secondary editing. ✅Exportable Mesh: Generated scenes can be exported as 3D meshes for direct import into mainstream game engines and modeling software. ✅Industry-Leading SOTA Evaluation: Surpasses state-of-the-art open-source models in generation quality. As the industry's first open-source model for physical simulation and explorable world generation, Hunyuan3D World Model 1.0 aims to foster a collaborative community ecosystem with developers and enthusiasts. ✨ Try it now: 🤗 Hugging Face:

Tencent Hy

23,203 次观看 • 1 年前

Competition 2: Mesh Generation 🦾 Until now, our subnet has focused on Gaussian splats. That work led to integrations with Unity, building the world’s largest 3D dataset, and early application deployments with real users and organic traffic growth. 🕹️ The next step is clear. Developers want native mesh generation that drops straight into existing game pipelines and unlocks real production use today. 🤖 Our competition format lets us move flexibly between goals, optimizing for near term commercial utility with meshes and balancing longer term research with Gaussian splat world models and digital twins. 📈 With significant open source mesh models releasing in the past weeks, the timing is right and the bar for miner innovation has never been higher. Mesh competition launches in 2 weeks!

Competition 2: Mesh Generation 🦾 Until now, our subnet has focused on Gaussian splats. That work led to integrations with Unity, building the world’s largest 3D dataset, and early application deployments with real users and organic traffic growth. 🕹️ The next step is clear. Developers want native mesh generation that drops straight into existing game pipelines and unlocks real production use today. 🤖 Our competition format lets us move flexibly between goals, optimizing for near term commercial utility with meshes and balancing longer term research with Gaussian splat world models and digital twins. 📈 With significant open source mesh models releasing in the past weeks, the timing is right and the bar for miner innovation has never been higher. Mesh competition launches in 2 weeks!

404

33,090 次观看 • 7 个月前

The Fondant Custom Normals Blender addon is being tested, and we're aiming for a 1.0 release next week! The first feature is the Weighted Normals + Laplacian Smoothing Geometry Nodes modifier. This let's you calculate Normals that are as clean as a nice quad mesh even if your topology is a mess and triangulated! We'll be following up with more tools to support creating high quality Normals for 3D anime and vtuber characters. We have an optimized adjustable Face Normal Transfer proxy mesh nearly ready to go. Check out the Docs to see more about the Addon's features and workflow (link in the reply.)

The Fondant Custom Normals Blender addon is being tested, and we're aiming for a 1.0 release next week! The first feature is the Weighted Normals + Laplacian Smoothing Geometry Nodes modifier. This let's you calculate Normals that are as clean as a nice quad mesh even if your topology is a mess and triangulated! We'll be following up with more tools to support creating high quality Normals for 3D anime and vtuber characters. We have an optimized adjustable Face Normal Transfer proxy mesh nearly ready to go. Check out the Docs to see more about the Addon's features and workflow (link in the reply.)

aVersionOfReality

54,088 次观看 • 1 年前

.Tencent Hy HY-World 2.0 has landed,fully OPEN SOURCE ! We kept hearing the same thing: world models look great, but you can't use the output. So we made one you can, real 3D assets you can edit, rearrange, and ship into production. Prompt to engine-ready 3D. For real this time： ✨Directly outputs editable, production-ready 3D assets ✨Seamlessly plugs into existing game pipelines ✨Multimodal input: text, image, videos 🪄Character mode: freely explore streets, buildings, and open worlds with realistic physics, collisions, and no time limits 🔗GitHub:

.Tencent Hy HY-World 2.0 has landed,fully OPEN SOURCE ! We kept hearing the same thing: world models look great, but you can't use the output. So we made one you can, real 3D assets you can edit, rearrange, and ship into production. Prompt to engine-ready 3D. For real this time： ✨Directly outputs editable, production-ready 3D assets ✨Seamlessly plugs into existing game pipelines ✨Multimodal input: text, image, videos 🪄Character mode: freely explore streets, buildings, and open worlds with realistic physics, collisions, and no time limits 🔗GitHub:

Tencent AI

116,648 次观看 • 4 个月前

So, today we have fast SDF sculpting + real-time AI in Unbound Loop. Old news🥱 Coming up next: -quad-view generation from sculpted geometry -image tweaks via nano🍌 -tripo HD & Low-Poly 3D generation There's more in the upcoming release, but these three deserve a closer look: Quad-View Generation Most platforms offer some version of this, but Loop has a key advantage, your sculpted model is the reference. That means less guessing from the generator. Though it’s not 100% foolproof, like any AI I guess? (I should stop stating the obvious every time). Image Tweaks via Chat Select any generated image and ask for fixes or changes in real time. Works great on unintended quad-view hallucinations, but also handy for quick iterations. Swapping colors, tweaking details, removing elements. Tripo 3D generator Especially the low-poly model, it consistently delivered fantastic game-ready topology when we tried it with our real-time AI output. And it's super fast.

So, today we have fast SDF sculpting + real-time AI in Unbound Loop. Old news🥱 Coming up next: -quad-view generation from sculpted geometry -image tweaks via nano🍌 -tripo HD & Low-Poly 3D generation There's more in the upcoming release, but these three deserve a closer look: Quad-View Generation Most platforms offer some version of this, but Loop has a key advantage, your sculpted model is the reference. That means less guessing from the generator. Though it’s not 100% foolproof, like any AI I guess? (I should stop stating the obvious every time). Image Tweaks via Chat Select any generated image and ask for fixes or changes in real time. Works great on unintended quad-view hallucinations, but also handy for quick iterations. Swapping colors, tweaking details, removing elements. Tripo 3D generator Especially the low-poly model, it consistently delivered fantastic game-ready topology when we tried it with our real-time AI output. And it's super fast.

Andrea Intg.

15,132 次观看 • 21 天前

World Model is trending— let's revisit our HunyuanWorld journey. We’ve been pioneering open-source 3D world generation in the past two months, and this ride’s only getting started. 🌍 📅 July: HunyuanWorld 1.0 📌 First open-source 3D world model compatible with CG pipelines (Unity/Unreal/Blender) 📌 Hit 2K+ GitHub stars in just two months ⭐—thank you for the love! 📅 August: 1.0-Lite 📌Same top-tier quality, running on consumer GPUs! 📅 September: 1.0-Voyager 📌 Direct 3D output + world memory—taking exploration further! Seamlessly integrated into CG pipelines with layered 3D modeling (assets, terrain, skybox) and fully open-sourced.. we’re fully committed to building open-source spatial intelligence for all! 🚀 💡 Why it matters? ✅ Seamless CG Pipeline Integration: Export generated 3D scenes as standard mesh formats, effortlessly integrating into industry-standard tools like Blender, Unity, and Unreal Engine for direct editing, animation, and physical simulation. ✅ Hierarchical Scene Editing: Deconstruct scenes into semantic layers (sky, background, foreground objects) via instance recognition and layer decomposition, allowing for atomic-level control—independently modify, relocate, or replace objects without rebuilding the entire world. Project page: Github: Amazing creations by Stijn Spanhove camenduru GENEL | AIを用いた動画制作 apolinario 🌐 とりにく Directive Creator 🪥 👇 #AI #3DGeneration #OpenSource #WorldModels #Hunyuan3D #HunyuanWorld

World Model is trending— let's revisit our HunyuanWorld journey. We’ve been pioneering open-source 3D world generation in the past two months, and this ride’s only getting started. 🌍 📅 July: HunyuanWorld 1.0 📌 First open-source 3D world model compatible with CG pipelines (Unity/Unreal/Blender) 📌 Hit 2K+ GitHub stars in just two months ⭐—thank you for the love! 📅 August: 1.0-Lite 📌Same top-tier quality, running on consumer GPUs! 📅 September: 1.0-Voyager 📌 Direct 3D output + world memory—taking exploration further! Seamlessly integrated into CG pipelines with layered 3D modeling (assets, terrain, skybox) and fully open-sourced.. we’re fully committed to building open-source spatial intelligence for all! 🚀 💡 Why it matters? ✅ Seamless CG Pipeline Integration: Export generated 3D scenes as standard mesh formats, effortlessly integrating into industry-standard tools like Blender, Unity, and Unreal Engine for direct editing, animation, and physical simulation. ✅ Hierarchical Scene Editing: Deconstruct scenes into semantic layers (sky, background, foreground objects) via instance recognition and layer decomposition, allowing for atomic-level control—independently modify, relocate, or replace objects without rebuilding the entire world. Project page: Github: Amazing creations by Stijn Spanhove camenduru GENEL | AIを用いた動画制作 apolinario 🌐 とりにく Directive Creator 🪥 👇 #AI #3DGeneration #OpenSource #WorldModels #Hunyuan3D #HunyuanWorld

Tencent HY

20,178 次观看 • 11 个月前

✨ 3d models are now LIVE on Photo AI 😊 You can now turn any AI photo you make into a 3d model by pressing [ 📦 Make 3d model ] And then you can view it inside Photo AI or download it as a .GLB 3d model file It's still very early in AI generated 3d model world but it's nice to have this feature working already As always, the models will keep improving, so this feature will keep getting better (like it did with video, it sucked before, now it's getting passable) Next would be nice to switch to .USDZ so you can load it straight into your iPhone with ARKit and put it in your room Available now for everyone on the Premium and Ultra plan

✨ 3d models are now LIVE on Photo AI 😊 You can now turn any AI photo you make into a 3d model by pressing [ 📦 Make 3d model ] And then you can view it inside Photo AI or download it as a .GLB 3d model file It's still very early in AI generated 3d model world but it's nice to have this feature working already As always, the models will keep improving, so this feature will keep getting better (like it did with video, it sucked before, now it's getting passable) Next would be nice to switch to .USDZ so you can load it straight into your iPhone with ARKit and put it in your room Available now for everyone on the Premium and Ultra plan

@levelsio

112,930 次观看 • 1 年前

Two weeks ago I fixed one of my teeth with algorithms I wrote a couple of years ago! I got hooked by 3D scanning when I started to work for a software shop in Zurich that was programming 3D computational geometry algorithms for denture scanning to produce crowns (and more). Back then, a typical reconstruction pipeline was like: scan the patient’s teeth using an intraoral scanner, reconstruct the surface mesh, design the restoration digitally, and finally mill the crown out of ceramic. We were working mostly with point clouds and meshes, but it wasn’t just math, it was craftsmanship translated into a digital process. Every micron mattered. You could literally see how a good algorithm meant a better fit in someone’s mouth. Gaussian Splatting isn’t about surface reconstruction, it’s about appearance reconstruction. It doesn’t care about explicit topology, it captures how light interacts with the scene. In a sense, it’s the opposite philosophy of the dental world: instead of modeling what the object is, it models how the object looks. 3D Gaussian Splatting enables applications like training self driving cars, teaching robots to understand their environment, creating virtual worlds, or monitoring real sites. It represents scenes as millions of small Gaussians rendered in real time without the need for meshes or textures. Coming from a world where precision geometry was everything, this shift felt natural. It’s still about reconstruction, but with a different goal: not manufacturing a perfect object, but reproducing how the world actually looks. Two weeks ago I got my first dental crown, made with the same software, reconstruction algorithms, and Swiss precision I once helped develop. I haven’t worked there in two years, but sitting in that chair and seeing the process from the other side was a proud moment. It reminded me why I love this field.

Two weeks ago I fixed one of my teeth with algorithms I wrote a couple of years ago! I got hooked by 3D scanning when I started to work for a software shop in Zurich that was programming 3D computational geometry algorithms for denture scanning to produce crowns (and more). Back then, a typical reconstruction pipeline was like: scan the patient’s teeth using an intraoral scanner, reconstruct the surface mesh, design the restoration digitally, and finally mill the crown out of ceramic. We were working mostly with point clouds and meshes, but it wasn’t just math, it was craftsmanship translated into a digital process. Every micron mattered. You could literally see how a good algorithm meant a better fit in someone’s mouth. Gaussian Splatting isn’t about surface reconstruction, it’s about appearance reconstruction. It doesn’t care about explicit topology, it captures how light interacts with the scene. In a sense, it’s the opposite philosophy of the dental world: instead of modeling what the object is, it models how the object looks. 3D Gaussian Splatting enables applications like training self driving cars, teaching robots to understand their environment, creating virtual worlds, or monitoring real sites. It represents scenes as millions of small Gaussians rendered in real time without the need for meshes or textures. Coming from a world where precision geometry was everything, this shift felt natural. It’s still about reconstruction, but with a different goal: not manufacturing a perfect object, but reproducing how the world actually looks. Two weeks ago I got my first dental crown, made with the same software, reconstruction algorithms, and Swiss precision I once helped develop. I haven’t worked there in two years, but sitting in that chair and seeing the process from the other side was a proud moment. It reminded me why I love this field.

MrNeRF

290,202 次观看 • 9 个月前

Tested Claude + Blender today with two real workflows. Sharing what actually happened. First one was a simple demo. Gave it one sentence to build a cyberpunk room. Geometry, lighting, camera, render. It got there, though not everything in the prompt landed perfectly. Good enough to show the concept, not a stress test. Second one was more interesting. Threw a raw photogrammetry scan at it. Massey Ferguson tractor, 250k faces, grass background everywhere, debris floating all over the place. Asked Claude to clean it up autonomously. It did the work. Removed 106 floating chunks, cut face count by 87%, stripped the grass, flipped the model upright, set up studio lighting and rendered. Technically it worked. But honest answer: the result wasn't clean enough for production. This kind of cleanup still needs the right tools and someone who knows what they're doing. So here's where it actually fits. Not the precise technical stuff. The setup work. The repetitive stuff. The things that take forever if you don't already know Blender. It won't replace your 3D artist. It replaces the boring part before they start.

Tested Claude + Blender today with two real workflows. Sharing what actually happened. First one was a simple demo. Gave it one sentence to build a cyberpunk room. Geometry, lighting, camera, render. It got there, though not everything in the prompt landed perfectly. Good enough to show the concept, not a stress test. Second one was more interesting. Threw a raw photogrammetry scan at it. Massey Ferguson tractor, 250k faces, grass background everywhere, debris floating all over the place. Asked Claude to clean it up autonomously. It did the work. Removed 106 floating chunks, cut face count by 87%, stripped the grass, flipped the model upright, set up studio lighting and rendered. Technically it worked. But honest answer: the result wasn't clean enough for production. This kind of cleanup still needs the right tools and someone who knows what they're doing. So here's where it actually fits. Not the precise technical stuff. The setup work. The repetitive stuff. The things that take forever if you don't already know Blender. It won't replace your 3D artist. It replaces the boring part before they start.

KIRI Engine - 3D Scanner App

61,093 次观看 • 3 个月前

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

25,802 次观看 • 7 个月前

World modeling and imitation learning have largely been considered two disparate worlds. In our recent work, Unified World Models, just accepted to #RSS2025, Chuning Zhu provides a dead-simple unifying solution: just train a joint diffusion model over actions and future states, but with *decoupled* diffusion time steps across these modalities. Manipulating these decoupled time steps then allows for marginalization or conditioning on actions or states; a single model can serve as a policy, forward dynamics model, video prediction model, or inverse dynamics model by simply setting diffusion timesteps carefully. The resulting model can leverage video datasets along with robot training data much more effectively, and shows improved robustness, generalization, and flexibility. This is exciting because it is frustratingly simple, scalable, and shows strong improvement on real-world robotics problems. Please refer to Chuning Zhu 's excellent thread for more details! More details/code can be found on our website and in the paper -

World modeling and imitation learning have largely been considered two disparate worlds. In our recent work, Unified World Models, just accepted to #RSS2025, Chuning Zhu provides a dead-simple unifying solution: just train a joint diffusion model over actions and future states, but with decoupled diffusion time steps across these modalities. Manipulating these decoupled time steps then allows for marginalization or conditioning on actions or states; a single model can serve as a policy, forward dynamics model, video prediction model, or inverse dynamics model by simply setting diffusion timesteps carefully. The resulting model can leverage video datasets along with robot training data much more effectively, and shows improved robustness, generalization, and flexibility. This is exciting because it is frustratingly simple, scalable, and shows strong improvement on real-world robotics problems. Please refer to Chuning Zhu 's excellent thread for more details! More details/code can be found on our website and in the paper -

Abhishek Gupta

11,430 次观看 • 1 年前

2023 was the year of AI avatars 2024 was the year of AI photos 2025 was the year of AI videos And I think it's becoming clear now that 2026 will be the year of AI world models Fully interactive explorable 3d worlds generated from one or multiple 2d images or a prompt In turn these 2d images can then be generated by AI too So soon you can generate fully explorable virtual 3d worlds based on your own imagination Next will be figuring out how to make those worlds interactive This is World Labs (unaffiliated, but I like it) As always a lot of big AI model companies are now working on the same thing: 3d world models, only World Labs has a real properly working demo (for now) Very exciting time again!

2023 was the year of AI avatars 2024 was the year of AI photos 2025 was the year of AI videos And I think it's becoming clear now that 2026 will be the year of AI world models Fully interactive explorable 3d worlds generated from one or multiple 2d images or a prompt In turn these 2d images can then be generated by AI too So soon you can generate fully explorable virtual 3d worlds based on your own imagination Next will be figuring out how to make those worlds interactive This is World Labs (unaffiliated, but I like it) As always a lot of big AI model companies are now working on the same thing: 3d world models, only World Labs has a real properly working demo (for now) Very exciting time again!

@levelsio

584,511 次观看 • 11 个月前

Dynamic workflows are a generalization of harnesses, automations, loops, routing, and graphs. It's the most powerful feature I have built into my agent orchestrator. Supports all kinds of patterns that leverage different agent backends (claude, codex, pi, hermes,...). It's a meta-harness approach that unlocks new forms of test-time compute. Example of use cases it supports: > LLM councils to get different perspectives from LLMs or plan more intensively > Dynamically routing tasks to different agents based on needs (e.g., cost efficiency and optimal intelligence) > Advisor/Judge + executor workflows and pretty much any complex graph-based pattern required by the task. I find it especially useful for long-running work and code reviewing. > Agent teams that talk to each other if needed for the task. I like to use this for AI editing, artifact creation, and other creative tasks. And I am sure it supports so many things that I haven't discovered yet. I got inspired by the dynamic workflow feature released by the Claude Code team. I had actually built it earlier this year but wanted to generalize it across different agent backends. I think this is going to become more popular in the coming days. I will share more of my findings soon.

Dynamic workflows are a generalization of harnesses, automations, loops, routing, and graphs. It's the most powerful feature I have built into my agent orchestrator. Supports all kinds of patterns that leverage different agent backends (claude, codex, pi, hermes,...). It's a meta-harness approach that unlocks new forms of test-time compute. Example of use cases it supports: > LLM councils to get different perspectives from LLMs or plan more intensively > Dynamically routing tasks to different agents based on needs (e.g., cost efficiency and optimal intelligence) > Advisor/Judge + executor workflows and pretty much any complex graph-based pattern required by the task. I find it especially useful for long-running work and code reviewing. > Agent teams that talk to each other if needed for the task. I like to use this for AI editing, artifact creation, and other creative tasks. And I am sure it supports so many things that I haven't discovered yet. I got inspired by the dynamic workflow feature released by the Claude Code team. I had actually built it earlier this year but wanted to generalize it across different agent backends. I think this is going to become more popular in the coming days. I will share more of my findings soon.

elvis

32,539 次观看 • 27 天前

Introducing RL Environment Creator Skill Now any one can create RL environments $ npx skills add adithya-s-k/RL_Envs_101 > You can create environments across multiple frameworks like OpenEnv, OpenReward, Verifiers, NemoGym ... > the repo has live working examples of environments that your coding agent can reference > The skill is design to first understand what type of model you are training and create an environment while keeping that in mind ps. There’s a lot more to building RL environments that can be used for training. One major aspect is the data, which this skill can’t directly solve. However, the skill will help with implementing tools, rewards, and other components of an RL environment, making it easier to go from idea to implementation quickly across different frameworks. Let me know if you’d be interested in a detailed, end-to-end blog/tutorial on building an environment and actually training a model for a useful use case.

Introducing RL Environment Creator Skill Now any one can create RL environments $ npx skills add adithya-s-k/RL_Envs_101 > You can create environments across multiple frameworks like OpenEnv, OpenReward, Verifiers, NemoGym ... > the repo has live working examples of environments that your coding agent can reference > The skill is design to first understand what type of model you are training and create an environment while keeping that in mind ps. There’s a lot more to building RL environments that can be used for training. One major aspect is the data, which this skill can’t directly solve. However, the skill will help with implementing tools, rewards, and other components of an RL environment, making it easier to go from idea to implementation quickly across different frameworks. Let me know if you’d be interested in a detailed, end-to-end blog/tutorial on building an environment and actually training a model for a useful use case.

Adithya S K

46,556 次观看 • 3 个月前

Thrilled to unveil Youmio, our new brand identity that represents the next evolution of what we’ve been building. Agents are the biggest technological leap since the internet, destined to transform crypto, games, and entertainment. With Youmio, we are shaping the agentic era, where agents learn, play and entertain in revolutionary ways. 🚀 So far, 2D entertainment and social media agents dominate the market. 3D agents are rare, requiring advanced AI and game engine skills. Yet 3D agents, especially those in game engines, unlock groundbreaking opportunities. Time to unleash them. Youmio empowers anyone to create and deploy valuable agents that are on-chain, cross-platform and ready for 3D worlds. Here’s how: ⭐️ Youmio Agents Youmio Agents lets anyone design and personalize 3D agents, equip them with powerful agentic capabilities, interact with them in unique ways and trade seamlessly within a cross-platform browser experience. 🕹️ Youmio Worlds Previously known as Today The Game, Youmio Worlds is a petri dish AI simulation where users build & co-inhabit beautiful, living 3D worlds with autonomous agents. Build dynamic worlds where players interact with intelligent agents, manage resources and participate in a player-agent marketplace. Ancient and Mythic Seeds are the most powerful entry points into the Youmio Worlds ecosystem, generating rare and beautiful worlds that unlock unique opportunities. 📡 Interoperable 3D Agents With Youmio, you’re not limited to our ecosystem. Using our API, developers can integrate Youmio agents into other experiences built in Unity and Unreal. On top of this, agents from other frameworks can also join Youmio, creating a truly interconnected metaverse. 🎭 Welcome to Limbo Meet Limbo, the first AI agent built using Youmio tech. Paired with the power of Youmio Worlds, we’re creating the Limboverse - a unique AI Big Brother setting where Limbo and your favorite and most valuable agents coexist in an ever-evolving, narrative-driven environment that you, the audience, will shape. $LIMBO is the most powerful entry point into the Limboverse and will be stakable on the Youmio Agents platform for unique rewards. Thanks for reading everyone and thanks for being on this amazing journey with us.🌱

Youmio

126,399 次观看 • 1 年前

🚀 The Segment Anything Model (SAM) has been upgraded to SAM2, featuring an efficient image encoder for segmenting images and videos. But does SAM2 outperform SAM1 in medical image and video segmentation? We're thrilled to present our paper "Segment Anything in Medical Images and Videos: Benchmark and Deployment"! We comprehensively benchmark SAM2 across 11 medical image modalities and videos. 📄 Paper: 💻 Code: **Highlights:** 1. SAM2 doesn’t always outperform SAM1 in 2D medical images, but excels in video segmentation, making it more accurate and efficient for 3D images, such as CT and MR scans. 2. MedSAM still outperforms SAM2 on most 2D modalities, but SAM2 surpasses MedSAM for 3D image segmentation in a slice-by-slice approach. 3. Segmentation performance varies with model size; sometimes the smallest model outperforms larger ones. 4. Fine-tuning SAM2 significantly boosts its performance for medical image segmentation. While SAM2 may struggle with challenging objects that have unclear boundaries or low contrast, it excels in generating good initial segmentation masks for common medical images and videos. However, the official interface doesn’t support medical data formats and has limitations on video length. To address this, we've developed a 3D Slicer Plugin and Gradio API for efficient 3D medical image and video segmentation. We invite you to try them out and provide feedback! 🔧 Deployment: - 3D Slicer Plugin: - Gradio API: (Note: Due to GPU limitations, the online API is available for only 12 hours and may be slow. We highly recommend deploying the Gradio API with your own computing resources: A big shoutout to Jun Ma (JunMa) who recently joined our UHN AI hub (UHN AI Hub) as Machine Learning Lead, and kudos to all co-authors: Sumin Kim, Feifei Li, Mohammed Baharoon (Mohammed Baharoon), Reza Asakereh, and Hongwei Lyu! This is true teamwork! Looking forward to collaborating with the community to advance 3D medical image and video segmentation foundation models! University Health Network U of T Department of Computer Science Department of Laboratory Medicine & Pathobiology Temerty Centre for AI in Medicine (T-CAIREM) Vector Institute #MedTech #AIinHealthcare #DeepLearning #MedicalImaging #SAM2 #MedSAM #AIResearch

🚀 The Segment Anything Model (SAM) has been upgraded to SAM2, featuring an efficient image encoder for segmenting images and videos. But does SAM2 outperform SAM1 in medical image and video segmentation? We're thrilled to present our paper "Segment Anything in Medical Images and Videos: Benchmark and Deployment"! We comprehensively benchmark SAM2 across 11 medical image modalities and videos. 📄 Paper: 💻 Code: Highlights: 1. SAM2 doesn’t always outperform SAM1 in 2D medical images, but excels in video segmentation, making it more accurate and efficient for 3D images, such as CT and MR scans. 2. MedSAM still outperforms SAM2 on most 2D modalities, but SAM2 surpasses MedSAM for 3D image segmentation in a slice-by-slice approach. 3. Segmentation performance varies with model size; sometimes the smallest model outperforms larger ones. 4. Fine-tuning SAM2 significantly boosts its performance for medical image segmentation. While SAM2 may struggle with challenging objects that have unclear boundaries or low contrast, it excels in generating good initial segmentation masks for common medical images and videos. However, the official interface doesn’t support medical data formats and has limitations on video length. To address this, we've developed a 3D Slicer Plugin and Gradio API for efficient 3D medical image and video segmentation. We invite you to try them out and provide feedback! 🔧 Deployment: - 3D Slicer Plugin: - Gradio API: (Note: Due to GPU limitations, the online API is available for only 12 hours and may be slow. We highly recommend deploying the Gradio API with your own computing resources: A big shoutout to Jun Ma (JunMa) who recently joined our UHN AI hub (UHN AI Hub) as Machine Learning Lead, and kudos to all co-authors: Sumin Kim, Feifei Li, Mohammed Baharoon (Mohammed Baharoon), Reza Asakereh, and Hongwei Lyu! This is true teamwork! Looking forward to collaborating with the community to advance 3D medical image and video segmentation foundation models! University Health Network U of T Department of Computer Science Department of Laboratory Medicine & Pathobiology Temerty Centre for AI in Medicine (T-CAIREM) Vector Institute #MedTech #AIinHealthcare #DeepLearning #MedicalImaging #SAM2 #MedSAM #AIResearch

Bo Wang

178,579 次观看 • 2 年前

🚀 Early Access to Sahara AI Studio is NOW OPEN! The next phase of our testnet is here with exclusive early access to our all-in-one platform designed to transform the AI development lifecycle into a streamlined, integrated experience. Here’s everything you need to know 👇 AI development is fragmented. Devs juggle multiple tools, leading to inefficiencies & high costs. Sahara AI Studio integrates the entire AI lifecycle—from datasets & model training to secure storage & scalable compute—into one seamless experience: 📊 Data Hub: Discover, Manage, and Leverage AI-Ready Datasets Access high-quality, domain-specific, open-source and proprietary datasets through an integrated marketplace. Developers can download, import, or label datasets, making it easier to train and fine-tune models or deploy RAG pipelines. Secure uploads and seamless workflow integration enhance the experience. 🤖 Model Hub: Discover, Customize and Scale AI Workflows with Ease Discover ready-to-use open-source and proprietary models, RAG pipelines, and customizable workflows. Developers can deploy models quickly while maintaining privacy and security through Sahara Vaults. 🖥️ Compute Hub: Flexible, Scalable Compute Resources for AI Innovation Access scalable and secure computing resources tailored to diverse AI workloads. Trusted Execution Environment (TEE) capabilities ensure data privacy, while integration with top compute providers offer flexibility for developers. 🔐 Vaults: Secure Storage for AI Assets Securely store, organize, and manage datasets, models, and other assets in an encrypted central repository. Vaults offer scalability, reproducibility, and user control over AI resources. This is more than just beta testing a platform—it's your chance to help shape the future of decentralized AI development. 📅 How to Apply We're onboarding select developers in a phased approach. Early Access spots are limited, so apply now:

🚀 Early Access to Sahara AI Studio is NOW OPEN! The next phase of our testnet is here with exclusive early access to our all-in-one platform designed to transform the AI development lifecycle into a streamlined, integrated experience. Here’s everything you need to know 👇 AI development is fragmented. Devs juggle multiple tools, leading to inefficiencies & high costs. Sahara AI Studio integrates the entire AI lifecycle—from datasets & model training to secure storage & scalable compute—into one seamless experience: 📊 Data Hub: Discover, Manage, and Leverage AI-Ready Datasets Access high-quality, domain-specific, open-source and proprietary datasets through an integrated marketplace. Developers can download, import, or label datasets, making it easier to train and fine-tune models or deploy RAG pipelines. Secure uploads and seamless workflow integration enhance the experience. 🤖 Model Hub: Discover, Customize and Scale AI Workflows with Ease Discover ready-to-use open-source and proprietary models, RAG pipelines, and customizable workflows. Developers can deploy models quickly while maintaining privacy and security through Sahara Vaults. 🖥️ Compute Hub: Flexible, Scalable Compute Resources for AI Innovation Access scalable and secure computing resources tailored to diverse AI workloads. Trusted Execution Environment (TEE) capabilities ensure data privacy, while integration with top compute providers offer flexibility for developers. 🔐 Vaults: Secure Storage for AI Assets Securely store, organize, and manage datasets, models, and other assets in an encrypted central repository. Vaults offer scalability, reproducibility, and user control over AI resources. This is more than just beta testing a platform—it's your chance to help shape the future of decentralized AI development. 📅 How to Apply We're onboarding select developers in a phased approach. Early Access spots are limited, so apply now:

Sahara AI 🔆

2,700,871 次观看 • 1 年前

This is not camera footage. It is a Blender character with 8K skin, detailed wrinkles, wet eyes, facial controls and enough micro-detail to make your brain keep waiting for the person to behave like a person. HumanPro packages that skin workflow into a Blender add-on instead of making artists rebuild it from scratch every time. The interesting AI angle is not “AI made a realistic girl.” A reusable 3D human can keep the same face across thousands of shots, then be relit, reposed, animated and dropped into completely different scenes without the identity drifting every six frames. Add Claude through Blender MCP and the workflow gets stranger: the model can help assemble scenes, adjust cameras and lighting, inspect renders and correct obvious visual problems, while the character system handles the skin and facial structure. It still does not remove the artist. Someone has to control expression, motion, lighting and the exact moment realism quietly turns into a very expensive mannequin. Most AI influencer projects are still fighting prompt consistency one image at a time. A rigged digital human is less magical, but probably much closer to how this becomes an actual production system.

This is not camera footage. It is a Blender character with 8K skin, detailed wrinkles, wet eyes, facial controls and enough micro-detail to make your brain keep waiting for the person to behave like a person. HumanPro packages that skin workflow into a Blender add-on instead of making artists rebuild it from scratch every time. The interesting AI angle is not “AI made a realistic girl.” A reusable 3D human can keep the same face across thousands of shots, then be relit, reposed, animated and dropped into completely different scenes without the identity drifting every six frames. Add Claude through Blender MCP and the workflow gets stranger: the model can help assemble scenes, adjust cameras and lighting, inspect renders and correct obvious visual problems, while the character system handles the skin and facial structure. It still does not remove the artist. Someone has to control expression, motion, lighting and the exact moment realism quietly turns into a very expensive mannequin. Most AI influencer projects are still fighting prompt consistency one image at a time. A rigged digital human is less magical, but probably much closer to how this becomes an actual production system.

Rina

109,122 次观看 • 1 个月前