Combining 3D and AI Blender & Stable Diffusion Workflow by Anton Tenitsky

Short on time? This 48-minute workflow shows you how to block out a room in Blender, feed depth maps into Stable Diffusion with ControlNet, and project the result back for a finished animated shot.

🎯 What you’ll learn

• Install and run Stable Diffusion Web UI locally with custom models from CivitAI
• Install and tune ControlNet for controllable image generation
• Build a room blockout in Blender and render depth passes for AI input
• Write effective prompts and embed them for consistent results
• Upscale AI images in Stable Diffusion and with Krea AI
• Project AI images back into Blender and match 3D models, lighting and shadows
• Set up camera animation, depth of field, bloom and compositing for final render

✅ Requirements

• Skills: Basic familiarity with Blender UI and navigation, no prior Stable Diffusion experience needed
• Tools: Blender 4.3+, Stable Diffusion Web UI with ControlNet extension, free Photopea in browser
• Hardware: PC capable of running Stable Diffusion locally, NVIDIA GPU with 6GB+ VRAM recommended, minimum 16GB RAM

📝 Description

This is not theory. It’s a working client workflow in under an hour. You start with a rough Blender greybox, render a depth map, and use it to steer Stable Diffusion so the AI actually respects your camera, walls and proportions.

You will see the full loop: blockout, depth pass blur in Photopea, ControlNet settings, prompt tweaks, generation, upscaling, then projection back into 3D. No guesswork, no random generations that you can’t reuse. If the depth is glitchy, you fix the preprocessor. If the image is soft, you upscale with latent or Krea AI.

The second half is where it gets practical for 3D artists. You pull a model from Sketchfab, drop it onto the AI background, match lighting and shadows with shadow catchers and light-linking in Blender 4.3, then push it through compositing with bloom, contrast and depth of field. Then you animate the camera and render it out.

You get 34 short chapters, all 4 project scenes with textures and models, plus the generated images and final animations to compare against. Easy to rewatch a specific step when you need it on a job.

🧑‍🎓 Who this course is for

• Aspiring 3D artists and designers who want to add AI to their process
• Game developers and environment artists who need fast background concepts
• Freelancers looking for quicker ways to deliver visuals to clients
• Anyone curious how 3D blocking and AI image generation work together

🧑‍🏫 About the Author

Anton Tenitsky is a practicing 3D artist working with Blender and AI-assisted visualization for real freelance clients. He uses this exact depth-map to render pipeline to deliver more variations faster without rebuilding scenes from scratch.

🏁 Final Result

• A photoreal AI-generated interior driven by your own Blender depth pass, composited with a 3D hero model, lit with matched shadows and bloom, and rendered as a short camera animation with depth of field — ready for portfolio or client pitch.