Use AI to create amazing 3D Animations! [Blender + Stable Diffusion]

15 Oct 202312:15

TLDRThis tutorial demonstrates a rapid workflow for creating 3D scenes in Blender using AI. It starts with a basic layout using primitive shapes to outline the scene's geometry, then employs a depth map to transfer the 3D information to AI for rendering. The process involves generating an image with AI, projecting it back onto the 3D model, and refining the scene with textures and animations. The technique allows for quick iterations and flexibility in scene development, offering a fun and efficient way to explore creative ideas in 3D design.


  • 🎨 Start with a basic 3D layout in Blender using primitive shapes to outline the scene's geometry.
  • 🌆 Create a rough model of a futuristic city on an island for establishing shots in films or games.
  • 📸 Set up the camera with appropriate resolution and aspect ratio, and use composition guides for better framing.
  • 🏞️ Enhance the scene by adding elements like mountains, city buildings, and vegetation using simple 3D modeling techniques.
  • 🌳 Utilize metaballs for creating organic shapes and vegetation canopies, and start with larger details before refining.
  • 🔍 Generate a depth map (z-depth pass) from the 3D layout to transfer spatial information for AI processing.
  • 🤖 Use AI (stable diffusion) with the depth map and a descriptive prompt to generate detailed images that match the 3D layout.
  • 🖼️ Import the AI-generated image back into Blender and project it onto the 3D geometry using camera projection.
  • 🌊 Animate elements like water and camera movements, and adjust the shading and materials to match the projected image.
  • 👽 Add new elements or change the environment by reusing the depth map workflow and generating new AI images.
  • 📚 The tutorial showcases a fast and fun way to iterate and visualize 3D scenes using AI, suitable for brainstorming and development.

Q & A

  • What is the main purpose of creating a 3D scene in Blender as described in the script?

    -The main purpose is to create a layout using primitive shapes to map out the basic geometry of the scene, which helps in understanding the final shot and serves as a sketch in 3D.

  • How does the script suggest using the 3D to 2D workflow for brainstorming and development?

    -The workflow allows users to quickly go from a layout to a final rendering, making it ideal for brainstorming and developing consistent environments for short film projects, video games, or simply to get started with Blender.

  • What is the first step in creating a 3D rendering according to the script?

    -The first step is to create a very rough model using primitive shapes to outline the basic geometry of the scene.

  • How does the script recommend creating a futuristic city environment in Blender?

    -By starting with a new plane as the ground plane, subdividing it to create an island, and then adding geometry for the city, mountains, and vegetation using simple shapes like cubes and cylinders.

  • What is a depth map in the context of 3D rendering?

    -A depth map is a black and white image that represents the spatial relationship of pixels, with bright pixels being closer to the camera and darker pixels being further away.

  • How can the depth map be utilized to transfer 3D information to AI for further processing?

    -The depth map can be rendered in Blender, saved, and then imported into an AI tool like Stable Diffusion to generate a detailed image based on the 3D layout.

  • What is the significance of using a control net in Stable Diffusion for this workflow?

    -A control net, enabled by using the depth map as a model, helps the AI generate an image that closely follows the 3D layout and desired style, leading to more accurate and interesting results.

  • How does the script suggest importing the AI-generated image back into Blender?

    -By using a technique called camera projection, where the camera acts as a projector to map the AI-generated texture onto the 3D scene's geometry.

  • What are some ways to enhance the final rendering after importing the AI image into Blender?

    -Enhancements can include adjusting the material properties, adding animation to elements like water, and using tools like Photoshop to modify or remove certain elements from the AI image.

  • How does the script suggest iterating and experimenting with the AI-generated images?

    -By going back to Stable Diffusion, changing the prompt, generating a new image, and projecting it into the Blender scene to quickly try out new looks and ideas.

  • What additional resources are offered for those interested in AI filmmaking based on the script?

    -The script mentions a course on the creator's Patreon page focused on learning traditional filmmaking and cinematography techniques with AI, where participants create their own AI short film.



🎨 Creating a 3D Layout in Blender

This paragraph outlines the process of creating a 3D layout in Blender, starting with the basics of using primitive shapes to map out the scene's geometry. It emphasizes the importance of understanding the final shot and the benefits of this workflow for brainstorming and developing consistent environments for various projects. The tutorial demonstrates how to create a rough version of a futuristic city on an island within a swamp, including the creation of a camera, adjusting its settings, and using composition guides to enhance the image. The paragraph also covers the addition of elements like mountains, city buildings, and vegetation to make the scene more interesting and the use of metaballs for organic shapes. The goal is to transition from layout to final rendering efficiently.


🤖 AI-assisted Image Generation with Stable Diffusion

This section delves into the use of AI in the creative process, specifically using Stable Diffusion to generate images based on the 3D layout created in Blender. It explains the process of creating a depth map, or z-depth pass, to transfer the 3D information to AI. The tutorial then guides through the use of Stable Diffusion's web interface, selecting a model, setting parameters, and using the depth map as a control net to generate an image that matches the desired style. The paragraph also discusses the importance of crafting a detailed prompt to achieve the best results and the iterative process of refining the image using various settings and prompts. Finally, it covers the process of importing the AI-generated image back into Blender using camera projection to texture the 3D scene.


🎥 Animation and Scene Enhancement in Blender

The final paragraph focuses on animating and enhancing the 3D scene in Blender. It begins with the animation of the camera, addressing issues like doubling effects and how to overcome them. The tutorial then moves on to animating water with a glossy shader and noise texture, using mapping nodes for control and creating a dynamic water effect. The paragraph highlights the ease of adding elements to the scene due to the pre-existing geometry and colors, showcasing the integration of AI-generated characters and objects. The tutorial concludes with various examples of how the scene can be modified, such as changing the environment from a swamp to a desert or altering the style to anime, emphasizing the flexibility and fun of using this technique. The creator also promotes a course on AI filmmaking, encouraging participants to learn traditional film techniques with AI and create their own short films.



💡3D Rendering

3D Rendering refers to the process of generating a two-dimensional image from a three-dimensional model. In the context of the video, it is the method used to create realistic images of a 3D scene, such as a futuristic city. The process involves creating a layout with basic geometry and then refining it with textures and lighting to achieve a final, visually appealing image.


Blender is an open-source 3D creation suite that allows users to design and create 3D models, animations, and visual effects. In the video, Blender is used as the primary tool for creating and rendering the 3D scene, from the initial layout to the final rendering with AI-enhanced textures.

💡AI Workflows

AI Workflows refer to the use of artificial intelligence tools and processes to streamline and enhance various tasks, such as content creation or data analysis. In the video, AI workflows are employed to speed up the creation of 3D scenes by using AI to generate textures and details based on a rough 3D model.


In 3D modeling and film production, a layout is the initial arrangement of the elements within a scene, including the placement of objects, characters, and the camera. It serves as a blueprint for the final composition. In the video, the layout is created using primitive shapes to map out the basic geometry of the scene, which is essential for understanding the final shot and composition.

💡Depth Map

A depth map, also known as a Z-depth pass, is a black and white image that represents the distance of objects from the camera in a 3D scene. Brighter pixels indicate objects closer to the camera, while darker pixels represent objects further away. In the video, the depth map is used to guide the AI in generating textures that match the 3D layout's geometry and spatial relationships.

💡Stable Diffusion

Stable Diffusion is a type of AI model that generates images from textual descriptions. It uses a process called diffusion to transform a random noise image into a detailed picture that matches the input text. In the video, Stable Diffusion is used to create textures and details for the 3D scene based on the depth map and a descriptive prompt.

💡Control Net

A control net in the context of AI image generation is a technique that uses additional input data to guide the output of the AI model. It helps to constrain the AI's creativity to produce results that align more closely with the desired outcome. In the video, the control net is the depth map that influences the AI to create an image that matches the 3D layout's structure.

💡Camera Projection

Camera projection is a technique in 3D modeling where a 2D image is projected onto the surfaces of a 3D model to create textures. This process is used to map the AI-generated image back onto the 3D scene in Blender, giving the model a detailed and realistic appearance.


Animation in 3D modeling refers to the process of creating the illusion of motion by manipulating objects, cameras, or other elements over time. In the video, animation is used to add life to the static 3D scene by moving the camera and creating dynamic effects like water movement and flying objects.


A shader is a type of computer program used in 3D graphics that calculates the appearance of objects based on lighting, materials, and other scene properties. Shaders determine how objects look under different lighting conditions and contribute to the overall visual quality of the rendered image. In the video, shaders are adjusted to improve the realism of the 3D scene, such as changing the specular and roughness values for more natural lighting effects.




Creating a 3D scene in Blender using a super simple and fun AI workflow.

Using primitive shapes to layout a rough model for better understanding of the final shot.

Transforming the rough 3D sketch into a detailed rendering by speeding up the process.

Establishing a futuristic city surrounded by a giant swamp as an example for creating an establishing shot.

Creating a ground plane and subdividing it to form an island for the city.

Setting up the camera with appropriate resolution and aspect ratio for the desired framing and composition.

Utilizing composition guides for better image composition, especially helpful for beginners.

Adding interest to the scene geometry by breaking the horizon line with mountains and creating a foreground.

Using cylinders and metaballs for creating symmetrical city structures and organic vegetation shapes.

Subdividing the plane and using sculpt tools to add more detail to the scene.

Creating a depth map or z-depth pass to transfer 3D information to AI for image generation.

Rendering the depth map with proper normalization to get the correct depth information.

Using Stable Diffusion with control net to generate an image from the depth map.

Importing the AI-generated image back into Blender and projecting it onto the 3D scene using camera projection.

Adjusting materials and shaders to match the AI image, enhancing the realism of the 3D scene.

Adding animation to the scene, such as camera movement and water animation, to bring the rendering to life.

Easily iterating and trying out new looks for the scene by changing the AI prompt and updating the shaders in Blender.

The potential for AI in filmmaking and the offer of a course on AI filmmaking and cinematography techniques.