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📢 LiteReality: Graphics-Ready 3D Scene Reconstruction from RGB-D Scans🏠✨ -> converts RGB-D scans into compact, realistic, and interactive 3D scenes — featuring high-quality meshes, PBR materials, and articulated objects. 📷 🌍

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Matthias Niessner

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23,766 görüntüleme • 1 yıl önce •via X (Twitter)

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📢GeomHair: Reconstruction of Hair Strands from Colorless 3D Scans📢 We present a novel method to reconstruct hair strands from colorless 3D scans by extracting orientation cues directly from the mesh surface geometry by finding local characteristic lines and from shaded renderings using a neural 2D line detector. We enhance the reconstruction with a diffusion prior trained on synthetic hair data and adapted to each scan using a tailored text prompt, allowing us to recover both simple and complex hairstyles without relying on color input. To support further research, we also introduce Strands400, the largest publicly available dataset of 3D hair strand reconstructions from real-world scans of 400 different people, featuring complicated hairstyles, such as ponytails and buns. 🌍 📷 Great work by Rachmadio Noval L. Artem Sevastopolsky Egor Zakharov @ness_pris
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📢GeomHair: Reconstruction of Hair Strands from Colorless 3D Scans📢 We present a novel method to reconstruct hair strands from colorless 3D scans by extracting orientation cues directly from the mesh surface geometry by finding local characteristic lines and from shaded renderings using a neural 2D line detector. We enhance the reconstruction with a diffusion prior trained on synthetic hair data and adapted to each scan using a tailored text prompt, allowing us to recover both simple and complex hairstyles without relying on color input. To support further research, we also introduce Strands400, the largest publicly available dataset of 3D hair strand reconstructions from real-world scans of 400 different people, featuring complicated hairstyles, such as ponytails and buns. 🌍 📷 Great work by Rachmadio Noval L. Artem Sevastopolsky Egor Zakharov @ness_pris

Matthias Niessner

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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 edit, optimize, and use across Blender, Maya, game engines, and other 3D workflows.
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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 edit, optimize, and use across Blender, Maya, game engines, and other 3D workflows.

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NVIDIA introduces Edify 3D AI model You can generate high quality 3D assets from text or image input under 2 minutes! With PBR materials, quad-mesh topologies, and 4k textures. 6 wild examples:

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📱✨ Scanned using only a smartphone, no manual work needed 🤯 Check out how our 3D scans perfectly match the real sneaker Left - Photo📷 Right - CGI 🖥️ Full PBR capture at its finest! 🔥👟 #3DScan #TechRevolution #SmartphoneMagic #PBR #MxrTech
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📱✨ Scanned using only a smartphone, no manual work needed 🤯 Check out how our 3D scans perfectly match the real sneaker Left - Photo📷 Right - CGI 🖥️ Full PBR capture at its finest! 🔥👟 #3DScan #TechRevolution #SmartphoneMagic #PBR #MxrTech

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RGB Human Videos -> Dexterous Manipulation Policies No teleoperation. No wearables. No robot interaction. The 🔑: Reliable 3D hand-object trajectory reconstruction and efficient action augmentation Fun collaboration led by Hongyi Chen
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This is RICULOUSLY good, TRELLIS 3D Generation model by Microsoft! 🔥 Generate high-quality 3D assets from text or image prompts. Supports various formats like Radiance Fields, 3D Gaussians, and meshes Available for FREE on Hugging Face!
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Today, we’re introducing Meta’s latest 3D foundation model, AssetGen 2.0, which was designed to create high-quality 3D assets from text and image prompts. AssetGen 2.0 consists of two models developed within Meta: one to generate 3D meshes and another to generate textures. Read More:

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SAM 3D Body is a CVPR 2026 award candidate paper from AI at Meta model recovers a full 3D human body mesh from a single RGB image you can run it automatically, or guide the reconstruction with masks and 2D keypoints thx to Niels Rogge for awesome demo idea

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3D AI is moving so fast.. this image to 3D AI tool can now generate super detailed 3D meshes with high quality texture.. it’s crazyyy link in comment
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📢New in ScanNet++: High-Res 360° Panos! Chandan Yeshwanth & Yueh-Cheng Liu have added pano captures for 956 ScanNet++ scenes, fully aligned with the 3D meshes, DSLR, and iPhone data - multiple panos per scene Check it out: Docs Code

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Developers at groundbreaking start-ups like Alpha3D and BOOM Interactive are making it possible to quickly and accurately convert 2D images into high-quality #3D models with #OpenUSD. Read more:
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Developers at groundbreaking start-ups like Alpha3D and BOOM Interactive are making it possible to quickly and accurately convert 2D images into high-quality #3D models with #OpenUSD. Read more:

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Meta dropped not just SAM-3 yesterday but also SAM-3D (for objects and humans)🤯 SAM 3D Body is a promptable model for recovering full-body 3D human meshes from a single image. Seems to be the new SOTA
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Meta dropped not just SAM-3 yesterday but also SAM-3D (for objects and humans)🤯 SAM 3D Body is a promptable model for recovering full-body 3D human meshes from a single image. Seems to be the new SOTA

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