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Using MeshyAI alongside Blender with Codex/Astra for 3D game creation is such an unlock for higher-fidelity characters (the models aren't great at procedurally creating characters in my experience) My workflow starts by generating high-res image refs (in t-pose and nothing else in background) of target characters in Codex/GPT Image...

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Rishi

8,013 subscribers

65,638 次观看 • 6 天前 •via X (Twitter)

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11 条评论

catman 的头像
catman5 天前

@MeshyAI the local studio page is a great touch, especially for catching broken rigs before they reach the game. does it also expose triangle count and animation previews, or is that still a separate Blender check?

Rishi 的头像
Rishi5 天前

@MeshyAI Yes!

好奇的小逸 的头像
好奇的小逸5 天前

@MeshyAI I am using Astra to create a Undead Dragon.

Rishi 的头像
Rishi4 天前

@MeshyAI Looks so sick

Mari Summers 💖✨📍RDC2026 的头像
Mari Summers 💖✨📍RDC20265 天前

@MeshyAI I needed this omg

Mari Summers 💖✨📍RDC2026 的头像
Mari Summers 💖✨📍RDC20265 天前

@MeshyAI THANK YOUUUU

MeshyAI 的头像
MeshyAI4 天前

Great!!!

Ryan Campbell 的头像
Ryan Campbell6 天前

@MeshyAI Nice!

GoalRival 的头像
GoalRival5 天前

@MeshyAI i've been seeing a lot of people mention Meshy. I'm going to have to try out this workflow you just posted once my usage resets!

Amanda King 的头像
Amanda King5 天前

@MeshyAI Tool sprawl is the hidden tax on this stack. Per-call access beats per-tool plans when Meshy is only for characters and the model is the glue. Actionway meters all of it off one balance.

COBOX 的头像
COBOX5 天前

@MeshyAI AI is changing how games are built. 🎮

相关视频

We’re excited to introduce the new A/T Pose generator for Image to 3D. We know everyone has their own rigging preference — so now, the choice is yours! Whether your pipeline is built for the classic T-Pose or you prefer the relaxed A-Pose, you can now select the exact format that fits your production line. It's all about giving you the flexibility to generate game-ready characters exactly how you need them. The feature is now integrated into Meshy 6 Preview. Try it out and take full control of your generations! 🚀
0:41

We’re excited to introduce the new A/T Pose generator for Image to 3D. We know everyone has their own rigging preference — so now, the choice is yours! Whether your pipeline is built for the classic T-Pose or you prefer the relaxed A-Pose, you can now select the exact format that fits your production line. It's all about giving you the flexibility to generate game-ready characters exactly how you need them. The feature is now integrated into Meshy 6 Preview. Try it out and take full control of your generations! 🚀

MeshyAI

57,007 次观看 • 9 个月前

Over the weekend, I added multiplayer "paint ball" dogfight to Tiny Skies, so players can fly around pelting each other with colourful paint balls, just for fun. I tried meshy and tripo to generate some 3D models for the game and the mesh vertices count are really high and lags the game a lot (probably because my game is a globe with thousands of objects - albeit mostly instanced). To my surprise, I found Gemini 3.1 Pro to be really quite good at generating good looking 3D models that are low in poly count. It generated 3D models at a much higher quality than Opus 4.6, Sonnet 4.6 and GPT 5.4. You can see the upgraded biplane models and some objects in the video below. #vibejam
0:23

Over the weekend, I added multiplayer "paint ball" dogfight to Tiny Skies, so players can fly around pelting each other with colourful paint balls, just for fun. I tried meshy and tripo to generate some 3D models for the game and the mesh vertices count are really high and lags the game a lot (probably because my game is a globe with thousands of objects - albeit mostly instanced). To my surprise, I found Gemini 3.1 Pro to be really quite good at generating good looking 3D models that are low in poly count. It generated 3D models at a much higher quality than Opus 4.6, Sonnet 4.6 and GPT 5.4. You can see the upgraded biplane models and some objects in the video below. #vibejam

Danny Limanseta

36,419 次观看 • 5 个月前

What is really useful is how GPT-6 Astra got better in spatial understanding. I'm still shocked how good it navigates 3D space. Here I gave it Blender MCP and Tripo P2.0 to generate optimized 3D models and put them together, rig and animate. Result is freaking awesome! Doing 3D objects procedurally with Astra is fun, but quality is not compared with what 3D Gen can do. Like you don't ask GPT to draw image with pen when there is GPT Image, same here. And token cost also speaks for it, 3D gen simply cheaper. But the way it assemble thing together, characters and scene, that is shocking ngl. And rigging of course, I have so much hope on it, it is most annoying part of 3d for me lol
0:35

What is really useful is how GPT-6 Astra got better in spatial understanding. I'm still shocked how good it navigates 3D space. Here I gave it Blender MCP and Tripo P2.0 to generate optimized 3D models and put them together, rig and animate. Result is freaking awesome! Doing 3D objects procedurally with Astra is fun, but quality is not compared with what 3D Gen can do. Like you don't ask GPT to draw image with pen when there is GPT Image, same here. And token cost also speaks for it, 3D gen simply cheaper. But the way it assemble thing together, characters and scene, that is shocking ngl. And rigging of course, I have so much hope on it, it is most annoying part of 3d for me lol

Stefan 3D AI

19,476 次观看 • 6 天前

I had an early access to GPT-6 Astra and I can say, everyone in the world now has a 3D designer at their fingertips. I gave it an image of a house and asked to create it in 3D with all the details including toys, appliances and furniture. This a full 3D model reconstruction in Blender with geometry that you can manually tweak and run 60fps as a locally rendered "game" on device.
0:20

I had an early access to GPT-6 Astra and I can say, everyone in the world now has a 3D designer at their fingertips. I gave it an image of a house and asked to create it in 3D with all the details including toys, appliances and furniture. This a full 3D model reconstruction in Blender with geometry that you can manually tweak and run 60fps as a locally rendered "game" on device.

Tom Krcha

1,433,744 次观看 • 9 天前

Grok 4.6 is looking really good for making 3D games! Here's a quick demo of a little cosy 3d game working right within Unity. Used Meshy for the character from a Grok Imagine 2.0 image. Just prompts. I didn't touch anything in Unity or Blender. Grok 4.6 just did everything via the Unity CLI. SFX and BGM with ElevenLabs.
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Grok 4.6 is looking really good for making 3D games! Here's a quick demo of a little cosy 3d game working right within Unity. Used Meshy for the character from a Grok Imagine 2.0 image. Just prompts. I didn't touch anything in Unity or Blender. Grok 4.6 just did everything via the Unity CLI. SFX and BGM with ElevenLabs.

Chong-U

226,250 次观看 • 1 个月前

img2threejs 1.5.1 is out 🚀 Checkout: This release introduces a new approach to image → 3D → Three.js. Image → Tripo → img2threejs → reconstructed geometry → Three.js Instead of using the generated 3D model as the final asset, img2threejs uses it as a reference to rebuild the character into a representation that can be generated and rendered directly in Three.js. No Blender workflow, and no GLB required as the final output. The animation in the demo is still a bit rough because this release is focused on reconstruction, not animation. I’ll be improving that in the next release. Still experimental, but this is a big step toward where I want img2threejs to go.
1:02

img2threejs 1.5.1 is out 🚀 Checkout: This release introduces a new approach to image → 3D → Three.js. Image → Tripo → img2threejs → reconstructed geometry → Three.js Instead of using the generated 3D model as the final asset, img2threejs uses it as a reference to rebuild the character into a representation that can be generated and rendered directly in Three.js. No Blender workflow, and no GLB required as the final output. The animation in the demo is still a bit rough because this release is focused on reconstruction, not animation. I’ll be improving that in the next release. Still experimental, but this is a big step toward where I want img2threejs to go.

Nick

117,187 次观看 • 19 天前

New clean 3D AI workflow Control Rig physics in UEFN! Been exploring some more hybrid AI workflows lately, and for 3D assets splitting the model into parts is kinda essential. This video shows my first test using AssetHub, one of the cleanest ways i've used to keep the whole generation process organized. It auto-detected the pose in my main image and broke it down into parts, then generated images for each. From there I can just iterate on each piece separately and generate the 3D models in one workflow. AssetHub is still in closed beta atm, so let me know if you want to try it out. Main reference image came from Grok Imagine. All the part images and high poly meshes were done in AssetHub, selected Tripo 3.1 as the main model. After that I ran it through Hunyuan 3D for retopo + unwrap. Final assembly in Blender. Baked normals from high to low poly. End result: under 60K tris, 3 materials, 2K textures. Also Control Rig physics in Unreal Engine are insane. It finally validates in UEFN too, so of course I had to test it out.
1:17

New clean 3D AI workflow Control Rig physics in UEFN! Been exploring some more hybrid AI workflows lately, and for 3D assets splitting the model into parts is kinda essential. This video shows my first test using AssetHub, one of the cleanest ways i've used to keep the whole generation process organized. It auto-detected the pose in my main image and broke it down into parts, then generated images for each. From there I can just iterate on each piece separately and generate the 3D models in one workflow. AssetHub is still in closed beta atm, so let me know if you want to try it out. Main reference image came from Grok Imagine. All the part images and high poly meshes were done in AssetHub, selected Tripo 3.1 as the main model. After that I ran it through Hunyuan 3D for retopo + unwrap. Final assembly in Blender. Baked normals from high to low poly. End result: under 60K tris, 3 materials, 2K textures. Also Control Rig physics in Unreal Engine are insane. It finally validates in UEFN too, so of course I had to test it out.

Jerome | InsaneUnreal

82,884 次观看 • 4 个月前

An Object is Worth 64x64 Pixels: Generating 3D Object via Image Diffusion discuss: We introduce a new approach for generating realistic 3D models with UV maps through a representation termed "Object Images." This approach encapsulates surface geometry, appearance, and patch structures within a 64x64 pixel image, effectively converting complex 3D shapes into a more manageable 2D format. By doing so, we address the challenges of both geometric and semantic irregularity inherent in polygonal meshes. This method allows us to use image generation models, such as Diffusion Transformers, directly for 3D shape generation. Evaluated on the ABO dataset, our generated shapes with patch structures achieve point cloud FID comparable to recent 3D generative models, while naturally supporting PBR material generation.
0:34

An Object is Worth 64x64 Pixels: Generating 3D Object via Image Diffusion discuss: We introduce a new approach for generating realistic 3D models with UV maps through a representation termed "Object Images." This approach encapsulates surface geometry, appearance, and patch structures within a 64x64 pixel image, effectively converting complex 3D shapes into a more manageable 2D format. By doing so, we address the challenges of both geometric and semantic irregularity inherent in polygonal meshes. This method allows us to use image generation models, such as Diffusion Transformers, directly for 3D shape generation. Evaluated on the ABO dataset, our generated shapes with patch structures achieve point cloud FID comparable to recent 3D generative models, while naturally supporting PBR material generation.

AK

66,559 次观看 • 2 年前

Tested this concepting workflow. ▶️ Converting a level design image to a 3D asset gallery image ▶️ re-generating segmented subjects into separate high quality images. ▶️ using these images to generate the 3D meshes. First time using 'for loops' in ComfyUI, works great and the prompts are updated for every segment. I used the Nano Banana 2 API node in ComfyUI to generate the final high quality images. Those SAM3 nodes are crazy btw, just set some points and it creates a mask! For the 3D model generation I used the new Tripo Smart Mesh tool, which is fast! The output is not perfect yet. I think in a lot of cases not production ready right now but that depends on the input image and the goal as well. For pre-production / concepting phase it's perfect and for far distance meshes it’s fine. I’m sure these tools keep improving, curious what we can work with in 3-6 months. Minimal cleanup and scaling in Blender and tested the meshes in UEFN / Unreal Engine. After creating the ComfyUI workflow it took less than an hour to do everything.
1:28

Tested this concepting workflow. ▶️ Converting a level design image to a 3D asset gallery image ▶️ re-generating segmented subjects into separate high quality images. ▶️ using these images to generate the 3D meshes. First time using 'for loops' in ComfyUI, works great and the prompts are updated for every segment. I used the Nano Banana 2 API node in ComfyUI to generate the final high quality images. Those SAM3 nodes are crazy btw, just set some points and it creates a mask! For the 3D model generation I used the new Tripo Smart Mesh tool, which is fast! The output is not perfect yet. I think in a lot of cases not production ready right now but that depends on the input image and the goal as well. For pre-production / concepting phase it's perfect and for far distance meshes it’s fine. I’m sure these tools keep improving, curious what we can work with in 3-6 months. Minimal cleanup and scaling in Blender and tested the meshes in UEFN / Unreal Engine. After creating the ComfyUI workflow it took less than an hour to do everything.

Jerome | InsaneUnreal

17,461 次观看 • 5 个月前

I created character assets and a world map for an Earthbound 3D game through mint it literally took me like 20 minutes to generate the world + characters as well as animate them The best part is I can download all of my assets in any 3D software like blender or unreal engine
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I created character assets and a world map for an Earthbound 3D game through mint it literally took me like 20 minutes to generate the world + characters as well as animate them The best part is I can download all of my assets in any 3D software like blender or unreal engine

mint

19,595 次观看 • 2 个月前

Here's a look behind the scenes of how I used a 3d model, generated from an image, as a "driver" for ai animation. In the near future we'll see more 3d tools that support these types of workflows, with much more emphasis on enhancing user input instead of just letting the ai do everything. I used the 3d model to generate keyframes that I then animated in Luma Dream. By using a 3d model with a diffusion "layer" done with Krea, I got quite high quality frames with a relatively high consistency as well since the AI didn't have to "hallucinate" that much. I upscaled and detailed the frames using Magnific. Using semi-detailed 3d models as drivers for gen ai is very powerful, and it allows us to use models that are sculpted in a more free-flowing type of workflow that doesn't rely so much on high surface detailing or very time-consuming finish, but instead relies more on gestural 3d sculpting. #art #ai
0:24

Here's a look behind the scenes of how I used a 3d model, generated from an image, as a "driver" for ai animation. In the near future we'll see more 3d tools that support these types of workflows, with much more emphasis on enhancing user input instead of just letting the ai do everything. I used the 3d model to generate keyframes that I then animated in Luma Dream. By using a 3d model with a diffusion "layer" done with Krea, I got quite high quality frames with a relatively high consistency as well since the AI didn't have to "hallucinate" that much. I upscaled and detailed the frames using Magnific. Using semi-detailed 3d models as drivers for gen ai is very powerful, and it allows us to use models that are sculpted in a more free-flowing type of workflow that doesn't rely so much on high surface detailing or very time-consuming finish, but instead relies more on gestural 3d sculpting. #art #ai

Martin Nebelong

48,280 次观看 • 2 年前

Astra built this three.js game with gorgeous graphics, then recreated every scene in Blender and made the trailer too. It feels like a massive upgrade from Sol for 3D graphics and front-end design. The UI feels way more polished and less like AI slop. The rocks, trees, monuments, and characters are all procedural code, keeping the game under 2 MB before the image and music assets. The level of autonomy is unbelievable. It needed very little steering, though I still had to keep pushing it to work harder on the details. The UI icons, buttons, and ornaments were made as transparent PNGs with GPT Image 2.
1:13

Astra built this three.js game with gorgeous graphics, then recreated every scene in Blender and made the trailer too. It feels like a massive upgrade from Sol for 3D graphics and front-end design. The UI feels way more polished and less like AI slop. The rocks, trees, monuments, and characters are all procedural code, keeping the game under 2 MB before the image and music assets. The level of autonomy is unbelievable. It needed very little steering, though I still had to keep pushing it to work harder on the details. The UI icons, buttons, and ornaments were made as transparent PNGs with GPT Image 2.

Meng To

134,358 次观看 • 7 天前

🔥 img2threejs × GPT-6 Astra × Hyper3D Live showcase: This is probably one of the most commercially valuable workflows I’ve tested so far. Image → Hyper3D → img2threejs → GPT-6 Astra → Interactive Three.js experience. 1/ Hyper3D handles the 3D reconstruction. 2/ img2threejs turns that result into a structured workflow that an AI coding model can actually work with. 3/ And GPT-6 Astra follows the img2threejs pipeline - turning the reconstructed asset into a structured, editable, and interactive Three.js experience with animation, VFX, lighting, and application logic. The important part isn’t just generating a 3D model, It’s what happens after the model exists. Instead of ending with a static asset, you can continue building around it with code: → Games → Interactive product experiences → 3D websites → Character showcases → Virtual worlds → Rapid prototypes 3D generation becomes the beginning of the workflow - not the final output. And when you combine high-quality reconstruction with an AI model capable of understanding and building the surrounding experience, the path from image → 3D → usable product becomes dramatically shorter. This is exactly the direction I want to push img2threejs. More experiments with OpenAI GPT-6 Astra × Hyper3D by Deemos are coming this month. 👨‍🍳
2:34

🔥 img2threejs × GPT-6 Astra × Hyper3D Live showcase: This is probably one of the most commercially valuable workflows I’ve tested so far. Image → Hyper3D → img2threejs → GPT-6 Astra → Interactive Three.js experience. 1/ Hyper3D handles the 3D reconstruction. 2/ img2threejs turns that result into a structured workflow that an AI coding model can actually work with. 3/ And GPT-6 Astra follows the img2threejs pipeline - turning the reconstructed asset into a structured, editable, and interactive Three.js experience with animation, VFX, lighting, and application logic. The important part isn’t just generating a 3D model, It’s what happens after the model exists. Instead of ending with a static asset, you can continue building around it with code: → Games → Interactive product experiences → 3D websites → Character showcases → Virtual worlds → Rapid prototypes 3D generation becomes the beginning of the workflow - not the final output. And when you combine high-quality reconstruction with an AI model capable of understanding and building the surrounding experience, the path from image → 3D → usable product becomes dramatically shorter. This is exactly the direction I want to push img2threejs. More experiments with OpenAI GPT-6 Astra × Hyper3D by Deemos are coming this month. 👨‍🍳

Nick

11,503 次观看 • 5 天前

A single 2D image → a 110,745-triangle 3D monster with 27 animations, running live in the browser. This is the Abyss Monster, built with img2threejs: The workflow: Image → 3D Reconstruction → Reference GLB + Specs → Rig → Animation Loops → VFX → Interactive Three.js 🔥 Inside this demo: 1/ 110,745 triangles reconstructed from the reference image 2/ 27 animation clips - Spin Flurry, Leap & Stomp, Charge, Collapse & more 3/ Reference-driven rig & animation workflow 4/ Dynamic lighting 5/ Real-time floating ember VFX 6/ Interactive WebGL character What I find most interesting is the workflow itself. The character and scene are built through a multi-prompt workflow, using visual references, GLB specs and animation loops to progressively construct the Three.js experience. Then, for the VFX, I used a single focused prompt to create the floating ember effect and integrate it into the scene. The final result is Three.js + TypeScript code - turning a visual reference into a programmable, interactive web experience. I’ll share the VFX prompt in the comments. 👇 #ThreeJS #WebGL #GameDev #TypeScript #Web3D #img2threejs
1:19

A single 2D image → a 110,745-triangle 3D monster with 27 animations, running live in the browser. This is the Abyss Monster, built with img2threejs: The workflow: Image → 3D Reconstruction → Reference GLB + Specs → Rig → Animation Loops → VFX → Interactive Three.js 🔥 Inside this demo: 1/ 110,745 triangles reconstructed from the reference image 2/ 27 animation clips - Spin Flurry, Leap & Stomp, Charge, Collapse & more 3/ Reference-driven rig & animation workflow 4/ Dynamic lighting 5/ Real-time floating ember VFX 6/ Interactive WebGL character What I find most interesting is the workflow itself. The character and scene are built through a multi-prompt workflow, using visual references, GLB specs and animation loops to progressively construct the Three.js experience. Then, for the VFX, I used a single focused prompt to create the floating ember effect and integrate it into the scene. The final result is Three.js + TypeScript code - turning a visual reference into a programmable, interactive web experience. I’ll share the VFX prompt in the comments. 👇 #ThreeJS #WebGL #GameDev #TypeScript #Web3D #img2threejs

Nick

11,302 次观看 • 11 天前

GPT-6 Astra can already plan, code, and build. The more interesting question is what happens when it can call a dedicated 3D tool at the exact moment a project needs an asset. So we connected Hyper3D Rodin MCP and asked Astra to build an interactive Solar System Explorer. Astra handled the app logic and integration. When it needed 3D models, it called Hyper3D Rodin directly. Hyper3D Rodin generated the required assets, and Astra brought them back into the project and continued building from there. That is where the workflow gets useful. Instead of stopping to search for assets or creating them manually, Astra can keep moving while Hyper3D handles the specialized 3D generation, with more control over the output and assets that are easier to integrate into the final project. The result is a browser-based solar system where the generated 3D models are part of the actual experience, not just outputs sitting in a model viewer.
0:39

GPT-6 Astra can already plan, code, and build. The more interesting question is what happens when it can call a dedicated 3D tool at the exact moment a project needs an asset. So we connected Hyper3D Rodin MCP and asked Astra to build an interactive Solar System Explorer. Astra handled the app logic and integration. When it needed 3D models, it called Hyper3D Rodin directly. Hyper3D Rodin generated the required assets, and Astra brought them back into the project and continued building from there. That is where the workflow gets useful. Instead of stopping to search for assets or creating them manually, Astra can keep moving while Hyper3D handles the specialized 3D generation, with more control over the output and assets that are easier to integrate into the final project. The result is a browser-based solar system where the generated 3D models are part of the actual experience, not just outputs sitting in a model viewer.

GitHub Projects Community

11,097 次观看 • 2 天前

, webgl experience fully made using fal the pipeline: GPT-Image-2 (or FLUX.2 Klein 9B for the live "create your own") 🦴 meshy v6 image-to-3d takes that → rigged GLB with a baked animation 🐾 GPT-Image-2/edit on the same character → companion creature image, color-locked to the character's palette → meshy v6 again (no rig) → static creature GLB 🪨 PATINA (fal-ai/patina/material/extract) takes the character image and outputs basecolor + normal + roughness + metalness for a per-character floor that matches their environment 🎬 Seedance 2.0 fast → 8s looping background video per character 📦 everything runs through gltf-transform (resize 1024 → webp q80 → draco) for ~95% size reduction → 400-800 KB GLBs 🖥️ the front-end is a single static index.html: Three.js scene, alpha-mapped marble disc with PlaneGeometry tessellation for real displacementMap depth, mirrored reflection plane, breathing animations on companions, palette-swap via CSS custom properties on character click 🧩 the whole recipe is published as a Claude Code skill fal-regenerate-3d so you can rebuild this yourself → ⚠ metrics shown are decorative
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, webgl experience fully made using fal the pipeline: GPT-Image-2 (or FLUX.2 Klein 9B for the live "create your own") 🦴 meshy v6 image-to-3d takes that → rigged GLB with a baked animation 🐾 GPT-Image-2/edit on the same character → companion creature image, color-locked to the character's palette → meshy v6 again (no rig) → static creature GLB 🪨 PATINA (fal-ai/patina/material/extract) takes the character image and outputs basecolor + normal + roughness + metalness for a per-character floor that matches their environment 🎬 Seedance 2.0 fast → 8s looping background video per character 📦 everything runs through gltf-transform (resize 1024 → webp q80 → draco) for ~95% size reduction → 400-800 KB GLBs 🖥️ the front-end is a single static index.html: Three.js scene, alpha-mapped marble disc with PlaneGeometry tessellation for real displacementMap depth, mirrored reflection plane, breathing animations on companions, palette-swap via CSS custom properties on character click 🧩 the whole recipe is published as a Claude Code skill fal-regenerate-3d so you can rebuild this yourself → ⚠ metrics shown are decorative

Lovis Odin

99,185 次观看 • 4 个月前

Tencent's Hunyuan 3D Studio is LIVE! 🎨 AI-powered 3D creation for professionals, slashing workflows from days to minutes.⚡️ Key Features: 🔹Text-to-3D: Generate controllable geometry (multi-view, multi-style, A pose, bbox-control) from text/images. 🔹Auto Part Split: Break models into 50+ editable components (hats, clothes, etc.) 🔹1-Min UV Unwrap: AI-driven, professional-grade UVs, no more manual fixes. 🔹PBR Textures: Precisely edit global or local textures with text or image prompts & professional material sphere generation. 🔹Auto Rigging: Quickly rig various characters, with specialized motion templates for human models. Hunyuan3D Studio is built to empower game developers, animators, and designers to create faster and smarter. 📄Tech Report: 👉🏻Try it now:
1:23

Tencent's Hunyuan 3D Studio is LIVE! 🎨 AI-powered 3D creation for professionals, slashing workflows from days to minutes.⚡️ Key Features: 🔹Text-to-3D: Generate controllable geometry (multi-view, multi-style, A pose, bbox-control) from text/images. 🔹Auto Part Split: Break models into 50+ editable components (hats, clothes, etc.) 🔹1-Min UV Unwrap: AI-driven, professional-grade UVs, no more manual fixes. 🔹PBR Textures: Precisely edit global or local textures with text or image prompts & professional material sphere generation. 🔹Auto Rigging: Quickly rig various characters, with specialized motion templates for human models. Hunyuan3D Studio is built to empower game developers, animators, and designers to create faster and smarter. 📄Tech Report: 👉🏻Try it now:

Tencent Hy

46,998 次观看 • 11 个月前

I started using Blender through MCP about two weeks ago, and I quickly realized that you can build almost anything with AI. This model was created using Blender, Hunyuan3D, Gemini, and ChatGPT. Here’s how I did it: I opened Gemini, uploaded an image of the Gundam model, and asked it to generate a clean front-view image. I uploaded that front view to ChatGPT and asked it to generate two additional angles: a back view and a 45-degree front-left view. I went to: I signed up with my email and translated the page into English. Then I opened Image to 3D and selected the multi-image option. You’ll see a diagram of a whale from several angles. Upload each reference image in its corresponding position, such as front, 45-degree front-left, and back. I selected the 1.5M-face option. This produces a very high-poly model, but don’t worry, we’ll fix that next. Once the generation is complete, download the model as a GLB file. From the Hunyuan homepage, open 3D Studio using one of the dropdown menus. Select the topology or retopology tool and upload your GLB. I chose the High setting to preserve as much detail as possible. After a few seconds, the model was retopologized. It kept most of its visual detail while using far fewer polygons. The original head and rifle didn’t look very good, so I generated them separately. I returned to ChatGPT and created dedicated reference images for the Gundam’s head and rifle. I generated each part individually in Hunyuan at the 1.5M setting, then ran both through the same retopology process. Next came the textures. Open the texture section, select the multi-image option, and upload the same reference images according to the whale orientation indicators. However, instead of using the original clean textures, I asked ChatGPT to recreate them with wear, rust stains, scratches, and other surface damage. This gave the Gundam a much older and more authentic appearance. Once every part was textured, I imported everything into Blender. You can ask Codex through MCP to remove the original head and rifle, or you can do it manually. Select the main model and press Tab to enter Edit Mode. Press 3 to enable face selection, then press C to activate Circle Select. Paint over the faces belonging to the original helmet or rifle. You can press X to delete those faces or P to separate them into another object. Then position the newly generated, more detailed head and rifle in their place. I demonstrate this process in one of my older videos. And that’s it. You now have a very cool 3D Gundam model! Afterward, I created the cockpit, separated the model into movable sections, and rigged everything for use in my Three.js game. That process deserves its own tutorial, though. If anyone wants to see it, let me know. Or just ask your AI, I guess. They seem to know everything these days. xD
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I started using Blender through MCP about two weeks ago, and I quickly realized that you can build almost anything with AI. This model was created using Blender, Hunyuan3D, Gemini, and ChatGPT. Here’s how I did it: I opened Gemini, uploaded an image of the Gundam model, and asked it to generate a clean front-view image. I uploaded that front view to ChatGPT and asked it to generate two additional angles: a back view and a 45-degree front-left view. I went to: I signed up with my email and translated the page into English. Then I opened Image to 3D and selected the multi-image option. You’ll see a diagram of a whale from several angles. Upload each reference image in its corresponding position, such as front, 45-degree front-left, and back. I selected the 1.5M-face option. This produces a very high-poly model, but don’t worry, we’ll fix that next. Once the generation is complete, download the model as a GLB file. From the Hunyuan homepage, open 3D Studio using one of the dropdown menus. Select the topology or retopology tool and upload your GLB. I chose the High setting to preserve as much detail as possible. After a few seconds, the model was retopologized. It kept most of its visual detail while using far fewer polygons. The original head and rifle didn’t look very good, so I generated them separately. I returned to ChatGPT and created dedicated reference images for the Gundam’s head and rifle. I generated each part individually in Hunyuan at the 1.5M setting, then ran both through the same retopology process. Next came the textures. Open the texture section, select the multi-image option, and upload the same reference images according to the whale orientation indicators. However, instead of using the original clean textures, I asked ChatGPT to recreate them with wear, rust stains, scratches, and other surface damage. This gave the Gundam a much older and more authentic appearance. Once every part was textured, I imported everything into Blender. You can ask Codex through MCP to remove the original head and rifle, or you can do it manually. Select the main model and press Tab to enter Edit Mode. Press 3 to enable face selection, then press C to activate Circle Select. Paint over the faces belonging to the original helmet or rifle. You can press X to delete those faces or P to separate them into another object. Then position the newly generated, more detailed head and rifle in their place. I demonstrate this process in one of my older videos. And that’s it. You now have a very cool 3D Gundam model! Afterward, I created the cockpit, separated the model into movable sections, and rigged everything for use in my Three.js game. That process deserves its own tutorial, though. If anyone wants to see it, let me know. Or just ask your AI, I guess. They seem to know everything these days. xD

Spectro

79,920 次观看 • 1 个月前