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This is amazing! You can now create high-quality 3D Scenes from a single image using Multi-Instance Diffusion Models (MIDI) 🔥

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Gradio

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41,770 görüntüleme • 1 yıl önce •via X (Twitter)

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Explore more about the MIDI Project: And keep an eye out as the Gradio app is being prepared here:

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OP3N brings you an immersive experience across multiple biomes, each with its unique game modes. Join the Adventure!

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Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior abs: project page:
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Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior abs: project page:

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Adobe is entering the image-to-3D game! Their new method, LRM, can create high-fidelity 3D meshes from a single image in just 5 seconds 🔥 It's trained on 1 million objects and is able to generate objects from real-world images and generative AI models.

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3DTopia-XL High-Quality 3D PBR Asset Generation via Primitive Diffusion demo: model: 3DTopia-XL scales high-quality 3D asset generation using Diffusion Transformer (DiT) built upon an expressive and efficient 3D representation, PrimX. The denoising process takes 5 seconds to generate a 3D PBR asset from text/image input which is ready for the graphics pipeline to use.
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3DTopia-XL High-Quality 3D PBR Asset Generation via Primitive Diffusion demo: model: 3DTopia-XL scales high-quality 3D asset generation using Diffusion Transformer (DiT) built upon an expressive and efficient 3D representation, PrimX. The denoising process takes 5 seconds to generate a 3D PBR asset from text/image input which is ready for the graphics pipeline to use.

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Skyfall-GS: Synthesizing Immersive 3D Urban Scenes from Satellite Imagery TL;DR: Skyfall-GS converts satellite images to explorable 3D urban scenes using diffusion models, with real-time rendering performance. Contributions: • We introduce Skyfall-GS, the first method to synthesize immersive, real-time, free-flight navigable 3D urban scenes solely from multi-view satellite imagery using generative refinement. • An open-domain refinement approach leverages pre-trained text-to-image diffusion models without domain-specific training. • A curriculum-learning-based iterative refinement strategy progressively enhances reconstruction quality from higher to lower viewpoints, significantly improving visual fidelity in occluded areas.

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DiffSplat Repurposing Image Diffusion Models for Scalable Gaussian Splat Generation DiffSplat is a generative framework to synthesize 3D Gaussian Splats from text prompts & single-view images in ⚡️ 1~2 seconds. It is fine-tuned directly from a pretrained text-to-image diffusion model.

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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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⚡️Generating 3DGS scenes in 5 seconds on a single GPU⚡️ #FlashWorld enables ⚡️*fast*⚡️ (10~100x faster than previous methods) and 🔥*high-quality*🔥 3D world generation, from a single image or text prompt. Code: Page:

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Image-Blaster is a Claude skill that can create an entire 3D environment from a single image. The special sauce here is that it also extracts key environment elements and converts them into their own separate 3D models. Full YT video:
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Image-Blaster is a Claude skill that can create an entire 3D environment from a single image. The special sauce here is that it also extracts key environment elements and converts them into their own separate 3D models. Full YT video:

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📽️➡️🏠 Can an image become a consistent 3D world? Video Diffusion Models look stunning, but 3D consistency is still a nightmare… #WorldStereo is different. We gave the AI a "3D brain" using Geometric Memories. The result? ✅ Zero flickering. ✅ Perfect 3D consistency.

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