workflow-templates-broken-zap-2026-06-08/site/knowledge/concepts/3d-generation.md

3D Generation

3D generation creates three-dimensional models — meshes, point clouds, or multi-view images — from text or image inputs. This enables rapid prototyping of 3D assets without manual modeling. In Hanzo Studio, several approaches exist: image-to-3D (lifting a single photo into a mesh), text-to-3D (generating a 3D object from a description), and multi-view generation (producing consistent views of an object that can be reconstructed into 3D).

How It Works in Hanzo Studio

• Key nodes involved: Model-specific loaders (TripoSR, InstantMesh, StableZero123), LoadImage, Save3D / Preview3D, CRM nodes
• Typical workflow pattern: Load image → Load 3D model → Run inference → Preview 3D result → Export mesh

Key Settings

• Inference steps: Number of denoising/reconstruction steps. More steps generally improve quality but increase generation time.
• Elevation angle: Camera elevation for multi-view generation, controlling the vertical viewing angle of the generated views.
• Guidance scale: How closely the model follows the input image or text. Higher values increase fidelity to the input but may reduce diversity.
• Output format: Export format for the 3D mesh — OBJ, GLB, and PLY are common options, each suited to different downstream tools.

Tips

• Clean single-object images on white or simple backgrounds work best for image-to-3D conversion.
• Multi-view approaches (like Zero123) often produce better geometry than single-view methods.
• Post-process generated meshes in Blender for cleanup, retopology, or texturing before production use.
• Start with TripoSR for quick results — it generates meshes in seconds and is a good baseline to compare against other methods.