Key Features

Two-stage diffusion framework for progressively refining 3D geometry from coarse structure to high-fidelity detail.
Scalable geometric refinement that improves surface quality, structural coherence, and fine-grained features across multiple stages.
Advanced data processing pipeline that prepares training shapes with consistent structure for robust model learning.
Watertight processing ensuring generated shapes have closed, well-defined surfaces suitable for simulation and manufacturing.
Quality filtering of 3D assets used in training to prioritize clean topology and reliable geometric patterns.
High-fidelity 3D shape generation aimed at producing detailed, production-ready geometry rather than low-resolution meshes.
Demonstrated comparisons with open-source 3D generation models to showcase improvements in detail and visual quality.
Comparative evaluations against commercial 3D models to position UltraShape 1.0 within the broader landscape of 3D shape generation systems.

At the core of UltraShape 1.0 is a scalable geometric refinement process that progressively improves the quality of generated shapes across stages, allowing the model to capture both global structure and fine-grained geometric details. The two-stage diffusion framework first establishes a reasonable coarse geometry and then refines it through dedicated steps that focus on surface consistency, shape completeness, and structural plausibility. This staged refinement makes the system more robust to artifacts and enables it to handle diverse shape categories while maintaining high resolution and fidelity in the final outputs.


UltraShape 1.0 is supported by an advanced data processing pipeline that emphasizes watertight processing and rigorous quality filtering, ensuring that training data and resulting shapes exhibit consistent, closed surfaces and usable topology. Watertight models are crucial for downstream tasks such as physics-based simulation, rendering, and manufacturing, and UltraShape 1.0 integrates this requirement directly into its preparation and generation pipeline. Alongside its technical report, the project provides access points for code and demos, as well as qualitative comparisons against both open-source and commercial 3D generation models, highlighting its strengths in geometric detail and overall shape quality.

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