HY-World 2.0 is a multi-modal world model framework for reconstructing, generating, and simulating navigable 3D worlds from diverse inputs. It accepts text prompts, single-view images, multi-view images, and videos, and produces 3D world representations rather than limiting output to flat video generation. For text and single-image inputs, it generates high-fidelity 3D Gaussian Splatting scenes through a multi-stage pipeline that includes panorama generation, trajectory planning, world expansion, and world composition. The system also improves reconstruction from multi-view images and video by upgrading its feed-forward 3D prediction components and its memory-aware view generation process. Another major part of the project is WorldLens, a rendering platform designed for interactive exploration with an engine-agnostic architecture, automatic image-based lighting, collision detection, and support for character interaction.

Features

  • Multi-modal input support for text images and video
  • Generation of navigable 3D Gaussian Splatting scenes
  • World reconstruction from multi-view images and videos
  • Multi-stage pipeline for panorama planning expansion and composition
  • Interactive rendering through the WorldLens platform
  • Support for physics collision and real-time exploration

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Categories

AI Models

License

MIT License

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Additional Project Details

Programming Language

Python

Related Categories

Python AI Models

Registered

2026-04-20