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Hy World 2 0 3d World Model

Tencent's HY-World 2.0 reconstructs 3D scenes from images or video, or generates them from text prompts. The core is WorldMirror 2.0, a 1.2B parameter feed-forward model that predicts depth, normals, camera parameters, and 3D Gaussian Splatting attributes in one pass. It handles 50K to 500K pixel resolution and supports prior injection if you already know camera poses. The skill wraps the Python pipeline with fp16 options for memory management and export to PLY or OBJ. Use this when you need to turn a folder of photos into a navigable 3D scene or prototype spatial AI tasks without manually rigging geometry. The Gradio app makes it approachable for quick tests.

skills.sh installs
314
GitHub stars
26
last updated
Jun 3, 2026

Install

$ npx -y skills add aradotso/trending-skills --skill hy-world-2-0-3d-world-model --agent claude-code

Installs into .claude/skills of the current project.

Files

HY-World 2.0 — 3D World Model Skill

Skill by ara.so — Daily 2026 Skills collection.

HY-World 2.0 is a multi-modal world model by Tencent Hunyuan that reconstructs, generates, and simulates 3D worlds. It accepts text, single-view images, multi-view images, and videos as input and produces 3D representations (meshes, 3D Gaussian Splattings, point clouds). Two core capabilities:

  • World Reconstruction (multi-view images / video → 3D): Powered by WorldMirror 2.0, a ~1.2B feed-forward model predicting depth, surface normals, camera parameters, 3D point clouds, and 3DGS attributes in a single forward pass.
  • World Generation (text / single image → 3D world): Four-stage pipeline — Panorama Generation (HY-Pano 2.0) → Trajectory Planning (WorldNav) → World Expansion (WorldStereo 2.0) → World Composition (WorldMirror 2.0 + 3DGS).

Installation

Requirements

  • Python 3.10
  • CUDA 12.4 (recommended)
  • PyTorch 2.4.0
# 1. Clone repository
git clone https://github.com/Tencent-Hunyuan/HY-World-2.0
cd HY-World-2.0

# 2. Create conda environment
conda create -n hyworld2 python=3.10
conda activate hyworld2

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Details

Repository
github.com/aradotso/trending-skills
First seen
Jun 3, 2026

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