1. Overview

AI Rendering is an all-in-one AI imaging suite in 3D Cloud Design that includes Rendering, AI Panorama and Style Transfer. Based on the current design scheme, users can quickly generate high-quality visuals, panoramic views, or restyle a space using a reference image.

One of the biggest advantages of this feature is the link between AI 3D model generation and AI Rendering. Users can first create a 3D model from a product image, then use AI Rendering to generate visuals and panoramas that closely reproduce the product’s appearance, materials and presentation within the space.

The rendering workflow is powered by advanced image models for finer detail, more realistic materials and better overall image quality. Style Transfer also lets users apply the architectural and finish style from a reference image to the original scene, making it faster to explore different looks and present alternative design directions.

 

2. Entry point

Path: AI tool > AI rendering

 

3. Feature introduction

Rendering: Generates an AI visual from the current camera view.

AI Panorama: Generates an AI panoramic view of the current design.

Style Transfer: Applies the architectural and finish style from a reference image to the original scene.

Users can view their remaining credits at the top of the page. The panel on the right shows generation history, and past results can also be viewed in the gallery.

 

(1) Rendering images

Rendering generates an AI image based on the current design and camera view.

Key features:

-Supports 3D models created from product images, helping preserve product details with high fidelity.

-Uses advanced image models to improve visual quality, material realism and overall image fidelity.

 

Typical use cases:

-Product visuals

-Interior visuals

-Customer communication

-Proposal presentations

 

 

(2) AI Panorama

AI Panorama generates a panoramic AI view of the current design, making it ideal for immersive space presentation.

 

Key features:

-Supports high-fidelity presentation of product models in panoramic views.

-Offers recommended ambience presets such as indoor daylight, morning, dusk and night.

 

Typical use cases:

-Panorama walkthroughs

-Customer presentations

-Showroom displays

-Full-space visual presentation

 

(3) Style Transfer

Style Transfer uses a reference image to apply a new architectural and finish style to the original scene.

 

Key features:

-Uses a reference image to transfer style to the current design.

-Preserves the original layout and main content while updating the overall look.

-Makes it easier to compare multiple styles without redesigning or re-rendering from scratch.

 

Typical use cases:

-Style replacement

-Design exploration

-Multi-option comparisons for customers

-Marketing visuals

 

4. Tips

Only have product images? Use AI 3D model generation + AI Rendering.

 

Not confident with lighting? Advanced rendering models help produce more realistic results with less manual setup.

 

 

 

8. FAQ

Q1: What is the difference between AI Rendering and traditional rendering?
AI Rendering uses AI to improve image quality quickly and reduce the time spent on manual lighting and repeated parameter adjustments. It is especially useful for fast product visuals and design presentation images.

Q2: Can 3D models generated from product images be used in AI Rendering?
Yes. This is one of the core strengths of the feature. After generating a 3D model from a product image, users can use AI Rendering and AI Panorama to create highly realistic visuals and panoramic views.

Q3: What is Style Transfer best used for?
It is ideal for quickly changing the architectural and finish style of a design based on a reference image, such as converting the original scene into a cream style, modern style, new Chinese style or light luxury style for comparison and customer communication.

Q4: Does image generation consume credits?
Yes. Different generation features may consume different amounts of credits. Please refer to the credit cost shown on the Generate Now button in the interface.

One content note: the model names are inconsistent in your Chinese draft. One section mentions stable_edit_n2 and fine_render_g2, while another mentions Nano Banana2 and GPT Image2. If this is external copy, I would either keep one consistent set or remove the model names entirely.