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    Lesson 2 of 5

    Text-to-3D & Image-to-3D Workflows

    From the course AI for 3D & Game Assets

    Let's get hands-on with generating 3D models from text descriptions and images.

    Text-to-3D with Meshy

    1. Go to meshy.ai and sign up (free tier available)
    2. Click "Text to 3D"
    3. Enter a description and select a style:

    Effective prompts:

    • "A medieval treasure chest with iron bands and a gold lock, fantasy game style"
    • "A low-poly pine tree with snow on branches, stylized"
    • "A sci-fi plasma rifle with glowing blue energy cells"
    • "A cute cartoon mushroom house with a red spotted cap"

    Style options:

    • Realistic, Cartoon, Low-poly, Voxel, Sculpture
    • Art style significantly affects output quality
    1. Generate — takes 1-3 minutes
    2. Preview the 3D model, rotate and inspect
    3. If satisfied, click "Refine" for higher quality
    4. Download in your preferred format

    Image-to-3D with Tripo

    Image-to-3D is generally more predictable:

    1. Generate or find a clear image of the object you want
    2. Upload to Tripo (tripo3d.ai)
    3. The AI reconstructs the 3D geometry
    4. Review from all angles — back and bottom may need manual refinement
    5. Export as GLB, OBJ, or FBX

    Tips for better image-to-3D:

    • Use clean, isolated images with plain backgrounds
    • Front-facing views with slight angle work best
    • Avoid complex occlusions (objects hidden behind other objects)
    • Higher-resolution images produce better geometry
    • Generate concept art with Midjourney first, then convert to 3D

    Multi-View Generation

    For better 3D consistency, some tools accept multiple views:

    1. Generate a front view of your object with an image AI
    2. Use the same prompt to generate side and back views
    3. Upload all views to the 3D generator
    4. AI uses multiple angles for more accurate reconstruction

    Prompt Engineering for 3D

    3D prompts benefit from specific details:

    • Shape: "cylindrical," "cubic," "organic," "angular"
    • Material: "metallic," "wooden," "stone," "glass," "fabric"
    • Style: "stylized," "realistic," "low-poly," "hand-painted"
    • Scale reference: "handheld," "furniture-sized," "building-sized"
    • Detail level: "simple," "detailed," "ornate," "minimalist"

    Bad prompt: "A sword" Good prompt: "A Viking longsword with a leather-wrapped grip, runic engravings on the blade, and a silver crossguard, realistic style"

    Batch Generation

    For populating game environments, generate asset libraries:

    • "10 different fantasy potion bottles" — Generate variations for variety
    • "A set of medieval tavern props" — Tables, chairs, mugs, candles
    • "Forest environment kit" — Trees, rocks, bushes, mushrooms, logs

    Key Takeaways

    • •Text-to-3D works best with specific descriptions including shape, material, and style
    • •Image-to-3D is more reliable — use clean, isolated images for best results
    • •Generate concept art with image AI first, then convert to 3D for a two-step workflow
    • •Multi-view input improves 3D reconstruction accuracy
    • •Batch generation creates asset libraries for game environments efficiently
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