What is the difference between large model 3D generation and traditional 3D modeling tools?

The difference between large model 3D generation and traditional 3D modeling tools lies in their approach, efficiency, and underlying technology.

Traditional 3D Modeling Tools:
These are software applications (e.g., Blender, Maya, 3ds Max) where users manually create 3D models by defining geometry, textures, and materials through tools like polygon modeling, sculpting, or parametric design. The process is highly skill-dependent, time-consuming, and requires expertise in 3D art or design.

Large Model 3D Generation:
This refers to AI-driven methods where large neural networks (often trained on vast 3D datasets) generate 3D models from text prompts, images, or minimal input. Techniques like diffusion models, NeRFs (Neural Radiance Fields), or transformer-based architectures can produce complex 3D structures with minimal human intervention. The output is faster, often requiring only a description or reference, but may need post-processing for precision.

Key Differences:

1. Input Method: Traditional tools require manual input (e.g., vertices, meshes), while large models generate 3D assets from text or images.
2. Speed & Efficiency: AI-generated 3D models are produced in seconds/minutes, whereas traditional modeling can take hours/days.
3. Skill Barrier: Traditional tools demand expertise, while AI methods are more accessible to non-experts.
4. Customization: Traditional modeling allows precise control, while AI-generated models may need refinement for specific use cases.

Example:

• Traditional: A game developer uses Blender to manually sculpt a character over weeks.
• AI-Based: A designer inputs "a futuristic cityscape at sunset" into an AI 3D generator, which produces a base model in minutes, later refined for gameplay.

For scalable 3D generation and storage, Tencent Cloud offers solutions like ModelArts (for AI training) and COS (Cloud Object Storage) to manage generated 3D assets efficiently. Additionally, Tencent Cloud's GPU-accelerated instances support high-performance AI model inference for real-time 3D generation.