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📢 Multi-View Image to 3D just got a major upgrade! Now your textures generate from multiple views too. So a few references of the same object bring the whole model back with much higher accuracy and consistency, from structure to texture.

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MeshyAI

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131,590 просмотров • 1 месяц назад •via X (Twitter)

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MVDream: Multi-view Diffusion for 3D Generation paper page: propose MVDream, a multi-view diffusion model that is able to generate geometrically consistent multi-view images from a given text prompt. By leveraging image diffusion models pre-trained on large-scale web datasets and a multi-view dataset rendered from 3D assets, the resulting multi-view diffusion model can achieve both the generalizability of 2D diffusion and the consistency of 3D data. Such a model can thus be applied as a multi-view prior for 3D generation via Score Distillation Sampling, where it greatly improves the stability of existing 2D-lifting methods by solving the 3D consistency problem. Finally, we show that the multi-view diffusion model can also be fine-tuned under a few shot setting for personalized 3D generation, i.e. DreamBooth3D application, where the consistency can be maintained after learning the subject identity.
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MVDream: Multi-view Diffusion for 3D Generation paper page: propose MVDream, a multi-view diffusion model that is able to generate geometrically consistent multi-view images from a given text prompt. By leveraging image diffusion models pre-trained on large-scale web datasets and a multi-view dataset rendered from 3D assets, the resulting multi-view diffusion model can achieve both the generalizability of 2D diffusion and the consistency of 3D data. Such a model can thus be applied as a multi-view prior for 3D generation via Score Distillation Sampling, where it greatly improves the stability of existing 2D-lifting methods by solving the 3D consistency problem. Finally, we show that the multi-view diffusion model can also be fine-tuned under a few shot setting for personalized 3D generation, i.e. DreamBooth3D application, where the consistency can be maintained after learning the subject identity.

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🔥 New Feature: Multi-View Images in One Click! 🎨 Turn text/image → consistent multi-views (powered by Flux Kontext) → high-accuracy 3D models in seconds! 🚀 Boost your 3D workflow today:
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🔥 New Feature: Multi-View Images in One Click! 🎨 Turn text/image → consistent multi-views (powered by Flux Kontext) → high-accuracy 3D models in seconds! 🚀 Boost your 3D workflow today:

MeshyAI

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How to split a 3D model into printable parts in one click? Here’s the full workflow with Meshy Auto Split: - Generate a draft model with Image-to-3D - Hit Auto Split. In 40 seconds, you get parts that follow the model’s natural structure - Download and open your slicer Every part comes out clean, watertight, and ready to print. Connectors? We hear you. Coming soon 👀
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How to split a 3D model into printable parts in one click? Here’s the full workflow with Meshy Auto Split: - Generate a draft model with Image-to-3D - Hit Auto Split. In 40 seconds, you get parts that follow the model’s natural structure - Download and open your slicer Every part comes out clean, watertight, and ready to print. Connectors? We hear you. Coming soon 👀

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📢 New AI Texturing is LIVE in Meshy 6 Preview! Experience enhanced fidelity & stronger style consistency for your Image-to-3D creations. If you haven't seen the upgrade, now's the time!
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📢 New AI Texturing is LIVE in Meshy 6 Preview! Experience enhanced fidelity & stronger style consistency for your Image-to-3D creations. If you haven't seen the upgrade, now's the time!

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Another use case with Nano Banana Pro (Video is fully narrated so don't forget to turn on the sound 🔊) Image to 3D Model For 3D Printing 1 - Generate an image of a vinyl toy character. I generated a character called Peelbert. 2 - Generate multiple outfits for Peelbert while retaining consistency. Nano Banana Pro's consistency and understanding of outfit changes is superb. 3 - Use Hunyuan 3.0 to do image to 3D model 4 - Save as STL and 3D Print. Nano Banana Pro to the real world 👍
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Another use case with Nano Banana Pro (Video is fully narrated so don't forget to turn on the sound 🔊) Image to 3D Model For 3D Printing 1 - Generate an image of a vinyl toy character. I generated a character called Peelbert. 2 - Generate multiple outfits for Peelbert while retaining consistency. Nano Banana Pro's consistency and understanding of outfit changes is superb. 3 - Use Hunyuan 3.0 to do image to 3D model 4 - Save as STL and 3D Print. Nano Banana Pro to the real world 👍

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📢 Intrinsic Image Fusion for Multi-View 3D Material Reconstruction 📢 We combine generative material priors with inverse path tracing: 1) define a parametric texture space 2) fuse monocular predictions across views into consistent textures 3) optimize low-dimensional parameters for physically-grounded reconstructions. The results are relightable PBR textures for 3D scenes: check out the result on a real-world 3D scan from the ScanNet++ dataset! 🌍 🎥 Great work by Peter Kocsis Lukas Höllein!

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3D AI is leveling up! Rodin 3D AI can create stunning, high-quality 3D models from just text or image inputs. And with its latest update, it can even generate 8K HDRI textures to bring your models to life. Check out the link in the comments!
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3D AI is leveling up! Rodin 3D AI can create stunning, high-quality 3D models from just text or image inputs. And with its latest update, it can even generate 8K HDRI textures to bring your models to life. Check out the link in the comments!

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46,061 просмотров • 1 год назад

Image to 3D, now in ANY pose! 🤸‍♂️ Simply upload your image + a pose reference photo. Meshy generates the model to match it perfectly. No complex rigging needed. Create 3D characters your way.
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V3D Video Diffusion Models are Effective 3D Generators Automatic 3D generation has recently attracted widespread attention. Recent methods have greatly accelerated the generation speed, but usually produce less-detailed objects due to limited model capacity or 3D data. Motivated by recent advancements in video diffusion models, we introduce V3D, which leverages the world simulation capacity of pre-trained video diffusion models to facilitate 3D generation. To fully unleash the potential of video diffusion to perceive the 3D world, we further introduce geometrical consistency prior and extend the video diffusion model to a multi-view consistent 3D generator. Benefiting from this, the state-of-the-art video diffusion model could be fine-tuned to generate 360degree orbit frames surrounding an object given a single image. With our tailored reconstruction pipelines, we can generate high-quality meshes or 3D Gaussians within 3 minutes. Furthermore, our method can be extended to scene-level novel view synthesis, achieving precise control over the camera path with sparse input views. Extensive experiments demonstrate the superior performance of the proposed approach, especially in terms of generation quality and multi-view consistency

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3D Alignment doesn't stop at geometry. This time, texture. Meshy 7 carries style, color and brushwork straight from your input image. Not a mesh that resembles your art. Your art, in 3D.❤️‍🔥

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📢ProcGen3D: Learning Neural Procedural Graphs for Image-to-3D Reconstruction Xinyi Zhang learns neural procedural graphs to generate high-fidelity 3D - MCTS-guided sampling maintains consistency with the input image, even from real images! Check it out:

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Using 3D assets with Gen-4 References is a simple way to bring highly detailed and specific models into your generative workflows for even more consistency and control. To do so, simply provide a location plate, a quick comp of your 3D model in that space and a style reference.
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Using 3D assets with Gen-4 References is a simple way to bring highly detailed and specific models into your generative workflows for even more consistency and control. To do so, simply provide a location plate, a quick comp of your 3D model in that space and a style reference.

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More Adobe Substance Modeler +AI experiments. Using quick, gestural 3d sketching to drive generative AI with much higher levels of creative control than you could ever get from a text prompt alone. The more detailed your 3d model is, the more you can leave the ai to just finish details like skin texture and individual strands of hair.. my model is obviously just a quick sketch😅 #art #ai

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56,612 просмотров • 2 лет назад

📢WorldMesh is accepted to #ECCV2026, and we're releasing the code today! 🎉 Led by mschneider456: navigable, multi-room 3D scenes from a text prompt, with a mesh scaffold conditioning image diffusion for global consistency + photorealistic detail 👇
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📢WorldMesh is accepted to #ECCV2026, and we're releasing the code today! 🎉 Led by mschneider456: navigable, multi-room 3D scenes from a text prompt, with a mesh scaffold conditioning image diffusion for global consistency + photorealistic detail 👇

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