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From 3d mesh optimization for games to accurate CAD to 3D conversions for enterprise and workflows that turbo-charge every 3D asset pipeline: InstaLOD is everything you need for the production and automatic optimization of 3D content.

17,283,631 次观看 • 3 年前 •via X (Twitter)

10 条评论

star wyse 的头像
star wyse3 年前

hey this is the thing that was used in sonic frontiers

InstaLOD 的头像
InstaLOD3 年前

Indeed, there's a video on the production on our YouTube channel!

VentiVR - Archived - 🦋 的头像
VentiVR - Archived - 🦋2 年前

Frontiers Mentioned

IZZY ♻️🥷®️ 的头像
IZZY ♻️🥷®️2 年前

Nice technology

Joe Dickenson | Co-Founder Candyland Carnage 的头像
Joe Dickenson | Co-Founder Candyland Carnage2 年前

This kind of thing in 3D world is insanely useful and time saving. Need a lot more stuff like this 🔥

Aezon 的头像
Aezon2 年前

This thing is super useful

ooOPizzaHeadOoo 的头像
ooOPizzaHeadOoo3 年前

does it keep quads?

🐲❄️🔥ShiningMew⚡️❄️🐲 的头像
🐲❄️🔥ShiningMew⚡️❄️🐲2 年前

hey i know this! it’s the tech used to make the lod models for sonic frontiers! really nice work!

Bluwolfblitz 的头像
Bluwolfblitz2 年前

Is there a free license for aspiring 3D Artists?

InstaLOD 的头像
InstaLOD2 年前

There is! You can get the pioneer license for free at - it's fully featured! 🤩

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DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior paper page: present DreamCraft3D, a hierarchical 3D content generation method that produces high-fidelity and coherent 3D objects. We tackle the problem by leveraging a 2D reference image to guide the stages of geometry sculpting and texture boosting. A central focus of this work is to address the consistency issue that existing works encounter. To sculpt geometries that render coherently, we perform score distillation sampling via a view-dependent diffusion model. This 3D prior, alongside several training strategies, prioritizes the geometry consistency but compromises the texture fidelity. We further propose Bootstrapped Score Distillation to specifically boost the texture. We train a personalized diffusion model, Dreambooth, on the augmented renderings of the scene, imbuing it with 3D knowledge of the scene being optimized. The score distillation from this 3D-aware diffusion prior provides view-consistent guidance for the scene. Notably, through an alternating optimization of the diffusion prior and 3D scene representation, we achieve mutually reinforcing improvements: the optimized 3D scene aids in training the scene-specific diffusion model, which offers increasingly view-consistent guidance for 3D optimization. The optimization is thus bootstrapped and leads to substantial texture boosting. With tailored 3D priors throughout the hierarchical generation, DreamCraft3D generates coherent 3D objects with photorealistic renderings, advancing the state-of-the-art in 3D content generation.

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161,530 次观看 • 2 年前