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🚨 This might be the biggest upgrade to AI 3D workflows. Most segmentation tools just cut meshes. Hyper3D's "Bang to Parts" feature: → automatically understands the 3D model, → & separates it into clean, editable components. This workflow is PRODUCTION-READY 👇

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Try the early preview of 3D mesh segmentation. Assistant now separates generated assets into individual parts, giving you full control to add behaviors, customize materials & textures, or swap pieces. Soon, you'll even be able to segment imported models.

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Stefan 3D AI

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AGAFE

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Super clean and efficient meshes by an AI? YES! The typical 3D Generative AI solutions produce lots of artifacts and usually way to many polygons due to volumetric approaches. In comparison “MeshGPT creates triangle meshes by autoregressively sampling from a transformer model that has been trained to produce tokens from a learned geometric vocabulary. These tokens can then be decoded into the faces of a triangle mesh. This method generates clean, coherent, and compact meshes, characterized by sharp edges and high fidelity.” Surely it is limited by the trained vocabulary but various versions can be trained for specific sets to create generative model libraries for certain object groups. Very promising approach with the high quality.

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René Schulte

20,772 просмотров • 2 лет назад

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Jerome | InsaneUnreal

17,267 просмотров • 4 месяцев назад

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Gabriele Romagnoli

20,126 просмотров • 8 месяцев назад

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One of the hardest things to achieve with AI is precise character motion. The new model by Kinetix, Kamo-1, is amazing at giving you far more control over your generations. It’s also the first 3D-conditioned model, so it understands the scene in 3D and gives you almost unlimited camera motion. Let me show you how to use it 👇

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