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🐌 SlugMeditate

Transforming calm thoughts into immersive VR journeys.

SlugMeditate is a calming VR experience that turns your thoughts into immersive worlds. Just type in a peaceful idea, and we use AI to generate visuals, turn them into video, and transform it into a 3D scene you can explore in virtual reality — all in your browser. It’s like a personalized meditation space, built from your own imagination.

🌟 Inspiration

We wanted to explore how emerging generative AI and VR technologies could support mindfulness and mental well-being. Many college students deal with stress and burnout — what if we could turn a simple reflection or intention into a deeply personal, calming VR experience?

Thus, SlugMeditate was born: a pipeline that transforms your thoughts into a 3D ambient escape.

✨ What It Does

SlugMeditate takes a text input (like "a peaceful forest at dusk") and transforms it into:

  1. Image Generation – Using Google Imagen 3, powered by Google AI Gemini, we generate visually rich and vivid images from the user’s prompt.
  2. Video Creation – These images are animated into smooth, cinematic video loops using Google AI Gemini Veo 2.
  3. 3D Scene Mapping – The generated video is converted into a volumetric 3D scene using Gaussian Splatting.
  4. VR Immersion – We render the 3D environment in-browser using Niantic Studio WebXR, paired with ambient music for a fully immersive and relaxing VR experience.
  5. Ambient Music Generation – Using Google MusicFX, we generate peaceful background music tailored to your prompt, completing the meditative vibe.

🧠 How We Built It

  • Text-to-Image: Generated with Imagen 3, part of Google AI Gemini's generative capabilities.
  • Image-to-Video: Animated using Gemini AI Veo 2 for cinematic smoothness and style.
  • 3D Reconstruction: Used Gaussian Splatting to map video into a navigable 3D environment.
  • VR Deployment: Built and displayed the immersive world using Niantic Studio WebXR.
  • Sound Design: Integrated calming ambient tracks to enhance the meditative experience.

Pipline

🧗 Challenges We Ran Into

  • A lot of the API documentation for Google tools (like Imagen 3 and Veo 2) was either outdated or didn’t work as expected, so we had to piece things together from multiple sources and experiment through trial and error.
  • We tried multiple methods of Gaussian Splatting, but hit limitations due to hardware constraints and time.
  • It was tricky to get the image-to-video prompting just right. If the camera motion didn’t pan correctly or stayed too static, the 3D reconstruction would break or look flat.
  • We were all new to Niantic Studio WebXR, so learning the ecosystem and figuring out how to display our 3D scene in a browser-based VR environment took some digging.
  • CruzHacks had unreliable Wi-Fi, which made working with cloud-based AI tools extra tough — we had to sync and generate assets whenever the connection let us.

🏆 Accomplishments We're Proud Of

  • Built a complete text-to-VR pipeline using cutting-edge generative AI in under 48 hours.
  • Successfully integrated Google AI Gemini tools with VR rendering frameworks.
  • Created an emotionally resonant experience combining creativity, tech, and wellness.
  • Learned and operationalized advanced tools like Imagen 3, Veo 2, and Gaussian Splatting quickly.

📚 What We Learned

  • Practical use of Google AI Gemini for generative media workflows.
  • How to bridge AI media generation with 3D spatial computing and VR rendering.
  • Rapid prototyping, team collaboration, and problem-solving under pressure.

🔮 What's Next

  • Interactive environments – Let users explore within the VR space.
  • Customization – Personalize music, ambient sounds, or guided meditations.
  • Performance tuning – Reduce generation and render time for real-time feedback.
  • Community gallery – Share and explore others' meditative scenes.

Built with love, curiosity, and caffeine by the SlugMeditate team at CruzHacks 2025
Powered by Google AI Gemini, Niantic Studio WebXR, and Gaussian Splatting.

Docker Setup:

  1. Run docker build -t python-env .
  2. docker run -it --rm -v "$(your path to directory):/app" python-env
    • for mac: docker run -it --rm -v "$PWD:/app" python-env
    • windows: docker run -it --rm -v "/$(pwd | sed 's/^C:\//; s/\///g'):/app" python-env

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