| --- |
| language: |
| - en |
| - zh |
| license: other |
| license_name: tencent-hy-world-2.0-community |
| license_link: https://github.com/Tencent-Hunyuan/HY-World-2.0/blob/main/License.txt |
| pipeline_tag: image-to-3d |
| library_name: hy-world-2 |
| tags: |
| - worldmodel |
| - 3d |
| - hy-world |
| extra_gated_eu_disallowed: true |
| --- |
| |
| <h1>HY-World 2.0: A Multi-Modal World Model for Reconstructing, Generating, and Simulating 3D Worlds</h1> |
|
|
| [English](README.md) | [简体中文](README_zh.md) |
|
|
| <p align="center"> |
| <img src="assets/teaser.png" width="95%" alt="HY-World-2.0 Teaser"> |
| </p> |
|
|
| <div align="center"> |
| <a href=https://3d.hunyuan.tencent.com/sceneTo3D target="_blank"><img src=https://img.shields.io/badge/Official%20Site-333399.svg?logo=homepage height=22px></a> |
| <a href=https://huggingface.co/tencent/HY-World-2.0 target="_blank"><img src=https://img.shields.io/badge/%F0%9F%A4%97%20Models-d96902.svg height=22px></a> |
| <a href=https://3d-models.hunyuan.tencent.com/world/ target="_blank"><img src= https://img.shields.io/badge/Page-bb8a2e.svg?logo=github height=22px></a> |
| <a href=https://arxiv.org/abs/2604.14268 target="_blank"><img src=https://img.shields.io/badge/Report-b5212f.svg?logo=arxiv height=22px></a> |
| <a href=https://modelscope.cn/models/Tencent-Hunyuan/HY-World-2.0 target="_blank"><img src=https://img.shields.io/badge/ModelScope-Models-624aff.svg height=22px></a> |
| <a href=https://discord.gg/dNBrdrGGMa target="_blank"><img src= https://img.shields.io/badge/Discord-white.svg?logo=discord height=22px></a> |
| <a href=https://x.com/TencentHunyuan target="_blank"><img src=https://img.shields.io/badge/Tencent%20HY-black.svg?logo=x height=22px></a> |
| <a href="#community-resources" target="_blank"><img src=https://img.shields.io/badge/Community-lavender.svg?logo=homeassistantcommunitystore height=22px></a> |
| </div> |
|
|
| <br> |
| <p align="center"> |
| <i>"What Is Now Proved Was Once Only Imagined"</i> |
| </p> |
|
|
| ## 🎥 Video |
| https://github.com/user-attachments/assets/b56f4750-25c9-48fb-83ff-d58526711463 |
|
|
| ## 🔥 News |
|
|
| - **[May 18, 2026]**: 🤗 Open-source World Generation inference code and WorldStereo 2.0 model weights! |
| - **[May 11, 2026]**: 🤗 Open-source HY-Pano 2.0 inference code and model weights! |
| - **[April 16, 2026]**: 🚀 Release HY-World 2.0 technical report & partial codes! |
| - **[April 16, 2026]**: 🤗 Open-source WorldMirror 2.0 inference code and model weights! |
|
|
|
|
| ## 📋 Table of Contents |
| - [📖 Introduction](#-introduction) |
| - [✨ Highlights](#-highlights) |
| - [🧩 Architecture](#-architecture) |
| - [📝 Open-Source Plan](#-open-source-plan) |
| - [🎁 Model Zoo](#-model-zoo) |
| - [🤗 Get Started](#-get-started) |
| - [🔮 Performance](#-performance) |
| - [🎬 More Examples](#-more-examples) |
| - [📚 Citation](#-citation) |
|
|
|
|
| ## 📖 Introduction |
|
|
| **HY-World 2.0** is a multi-modal world model framework for **world generation** and **world reconstruction**. It accepts diverse input modalities — text, single-view images, multi-view images, and videos — and produces 3D world representations (meshes / Gaussian Splattings). It offers two core capabilities: |
|
|
| - **World Generation** (text / single image → 3D world): syntheses high-fidelity, navigable 3D scenes through a four-stage method —— a)  with HY-Pano 2.0, b)  with WorldNav, c)  with WorldStereo 2.0, and d)  with WorldMirror 2.0 & 3DGS learning. |
| - **World Reconstruction** (multi-view images / video → 3D): Powered by WorldMirror 2.0, a unified feed-forward model that simultaneously predicts depth, surface normals, camera parameters, 3D point clouds, and 3DGS attributes in a single forward pass. |
|
|
| HY-World 2.0 is an **open-source state-of-the-art** world model. We released all model weights, code, and technical details to facilitate reproducibility and advance research in this field. |
|
|
| ### Why 3D World Models? |
|
|
| Existing world models, such as Genie 3, Cosmos, and HY-World 1.5 (WorldPlay+WorldCompass), generate pixel-level videos — essentially "watching a movie" that vanishes once playback ends. **HY-World 2.0 takes a fundamentally different approach**: it directly produces editable, persistent 3D assets (meshes / 3DGS) that can be imported into game engines like Blender/Unity/Unreal Engine/Isaac Sim — more like "building a playable game" than recording a clip. This paradigm shift natively resolves many long-standing pain points of video world models: |
|
|
| | | Video World Models | 3D World Model (HY-World 2.0) | |
| |--|---|---| |
| | **Output** | Pixel videos (non-editable) | Real 3D assets — meshes / 3DGS (fully editable) | |
| | **Playable Duration** | Limited (typically 1 min) | Unlimited — assets persist permanently | |
| | **3D Consistency** | No (flickering, artifacts across views) | Native — inherently consistent in 3D | |
| | **Real-Time Rendering** | Requires per-frame inference; high latency | Consumer GPUs can render in real time | |
| | **Controllability** | Weak (imprecise character control, no real physics) | Precise — zero-error control, real physics collision, accurate lighting | |
| | **Inference Cost** | Accumulates with every interaction | One-time generation; rendering cost ≈ 0 | |
| | **Engine Compatibility** | ✗ Video files only | ✓ Directly importable into Blender / UE / Isaac Engine | |
| | | $\color{IndianRed}{\textsf{Watch a video, then it's gone}}$ | $\color{RoyalBlue}{\textbf{Build a world, keep it forever}}$ | |
|
|
|
|
| <table align="center" style="border: none;"> |
| <tr> |
| <td align="center" width="50%"><img src="assets/screenshot_1.gif" width="100%"></td> |
| <td align="center" width="50%"><img src="assets/screenshot_2.gif" width="100%"></td> |
| </tr> |
| <tr> |
| <td align="center" width="50%"><img src="assets/screenshot_7.gif" width="100%"></td> |
| <td align="center" width="50%"><img src="assets/screenshot_8.gif" width="100%"></td> |
| </tr> |
| </table> |
| |
| <p align="center"><em>All above are <strong>real 3D assets</strong> (not generated videos) and entirely created by HY-World 2.0 -- captured from live real-time interaction.</em></p> |
|
|
| ## ✨ Highlights |
|
|
| - **Real 3D Worlds, Not Just Videos** |
|
|
| Unlike video-only world models (e.g., Genie 3, HY World 1.5), HY-World 2.0 generates **real 3D assets** — 3DGS, meshes, and point clouds — that are freely explorable, editable, and directly importable into **Unity / Unreal Engine / Isaac**. From a single text prompt or image, create navigable 3D worlds with diverse styles: realistic, cartoon, game, and more. |
|
|
| <p align="center"> |
| <img src="assets/mesh_en.gif" width="95%"> |
| </p> |
|
|
|
|
| - **Instant 3D Reconstruction from Photos & Videos** |
|
|
| Powered by **WorldMirror 2.0**, a unified feed-forward model that predicts dense point clouds, depth maps, surface normals, camera parameters, and 3DGS from multi-view images or casual videos in a single forward pass. Supports flexible-resolution inference (50K–500K pixels) with SOTA accuracy. Capture a video, get a digital twin. |
|
|
| <p align="center"> |
| <img src="assets/recon_en.gif" width="95%"> |
| </p> |
|
|
| - **Interactive Character Exploration** |
|
|
| Go beyond viewing — **play inside your generated worlds**. HY-World 2.0 supports first-person navigation and third-person character mode, enabling users to freely explore AI-generated streets, buildings, and landscapes with physics-based collision. Go to [our product page](https://3d.hunyuan.tencent.com/sceneTo3D) for free try (). |
|
|
| <p align="center"> |
| <img src="assets/interactive.gif" width="95%"> |
| </p> |
|
|
|
|
| ## 🧩 Architecture |
| - **Refer to our tech report for more details** |
|
|
| A systematic pipeline of HY-World 2.0 — *Panorama Generation* (HY-Pano-2.0) → *Trajectory Planning* (WorldNav) → *World Expansion* (WorldStereo 2.0) → *World Composition* (WorldMirror 2.0 + Splattings Learning) — that automatically transforms text or a single image into a high-fidelity, navigable 3D world (3DGS/mesh outputs). |
|
|
| <p align="center"> |
| <img src="assets/overview.png" width="95%"> |
| </p> |
|
|
|
|
| ## 📝 Open-Source Plan |
|
|
| - [x] Technical Report |
| - [x] WorldMirror 2.0 Code & Model Checkpoints |
| - [x] Full Inference Code for World Generation (WorldNav + WorldStereo + World Composition) |
| - [x] Panorama Generation (HY-Pano 2.0) Model & Code |
| - [x] World Expansion (WorldStereo 2.0) Model & Code |
|
|
|
|
| ## 🎁 Model Zoo |
|
|
| ### World Reconstruction — WorldMirror Series |
|
|
| | Model | Description | Params | Date | Hugging Face | |
| |-------|-------------|--------|------|--------------| |
| | WorldMirror-2 [new] | Multi-view / video → 3D reconstruction | ~1.2B | 2026 | [Download](https://huggingface.co/tencent/HY-World-2.0/tree/main/HY-WorldMirror-2.0) | |
| | WorldMirror-1 | Multi-view / video → 3D reconstruction (legacy) | ~1.2B | 2025 | [Download](https://huggingface.co/tencent/HunyuanWorld-Mirror/tree/main) | |
|
|
| ### Panorama Generation — HY-Pano Series |
|
|
| | Model | Description | Params | Date | Hugging Face | |
| |-------|-------------|--------|------|--------------| |
| | HY-Pano-2 [new] | Text / image → 360° panorama | ~80B | 2026 | [Download](https://huggingface.co/tencent/HY-World-2.0/tree/main/HY-Pano-2.0) | |
| | HY-Pano-2-Qwen [new] | Text / image → 360° panorama | ~425M | 2026 | [Download](https://huggingface.co/tencent/HY-World-2.0/blob/main/HY-Pano-2.0/pytorch_lora_weights.safetensors) | |
|
|
| ### World Expansion — WorldStereo Series |
|
|
| | Model | Description | Params | Date | Hugging Face | |
| |-----------------|-------------|-----|------|--------------| |
| | WorldStereo-2 [new] | Panorama → 3DGS world | ~17B | 2026 | [Download](https://huggingface.co/hanshanxue/WorldStereo/tree/main) | |
|
|
| We recommend referring to our previous works, [WorldStereo](https://github.com/FuchengSu/WorldStereo) and [WorldMirror](https://github.com/Tencent-Hunyuan/HunyuanWorld-Mirror), for background knowledge on 3D world generation and reconstruction. |
|
|
| ## 🤗 Get Started |
|
|
| ### Install Requirements |
|
|
| We recommend **CUDA 12.8** and **Python 3.11+**. The easiest path is to prepare one shared environment, first make **World Reconstruction (WorldMirror 2.0)** work, and then install the extra components required by **World Generation**. |
|
|
| #### 1. Create the shared environment |
|
|
| ```bash |
| git clone https://github.com/Tencent-Hunyuan/HY-World-2.0 |
| cd HY-World-2.0 |
| |
| conda create -n hyworld2 python=3.11.15 |
| conda activate hyworld2 |
| ``` |
|
|
| #### 2. Install World Reconstruction dependencies |
|
|
| After this step, the environment is ready for **worldrecon / WorldMirror 2.0**. |
|
|
| ```bash |
| # Base dependencies shared by worldrecon and worldgen |
| pip install -r requirements.txt |
| |
| # Recommended: install the custom gsplat variant once for both worldrecon and worldgen |
| cd hyworld2/worldgen/third_party/gsplat_maskgaussian |
| pip install -e . --no-build-isolation |
| cd ../../../../ |
| ``` |
|
|
| If you only need **worldrecon** and want a simpler fallback, official `gsplat` is also supported: |
|
|
| ```bash |
| pip install git+https://github.com/nerfstudio-project/gsplat.git |
| ``` |
|
|
| Install **one** FlashAttention backend: |
|
|
| ```bash |
| # Recommended for Hopper GPUs: FlashAttention-3 |
| git clone https://github.com/Dao-AILab/flash-attention.git |
| cd flash-attention/hopper |
| python setup.py install |
| cd ../../ |
| rm -rf flash-attention |
| ``` |
|
|
| ```bash |
| # Simpler alternative: FlashAttention-2 |
| pip install flash-attn --no-build-isolation |
| ``` |
|
|
| #### 3. Add extra World Generation dependencies |
|
|
| Run the following extra steps only if you need **worldgen**. These commands assume the shared `hyworld2` environment above is already active. |
|
|
| ```bash |
| # Git-based dependencies require torch/CUDA to be installed first |
| pip install --no-build-isolation -r requirements_git.txt |
| |
| # recastnavigation is managed as a git submodule |
| git submodule update --init --recursive |
| |
| # Recast navmesh extension for trajectory planning |
| cd hyworld2/worldgen/third_party/navmesh |
| pip install . --no-build-isolation |
| cd ../../../../ |
| ``` |
|
|
| For **HY-Pano-2** installation, please refer to **[hyworld2/panogen/README.md](hyworld2/panogen/README.md)**. |
|
|
| ### Code Usage — Panorama Generation (HY-Pano-2) |
|
|
| For full documentation and CLI reference, see **[hyworld2/panogen/README.md](hyworld2/panogen/README.md)**. |
|
|
| We provide a `diffusers`-like Python API for HY-Pano 2.0. Model weights are automatically downloaded from Hugging Face on first run. |
|
|
| ```python |
| from pipeline import HunyuanPanoPipeline |
| |
| pipeline = HunyuanPanoPipeline.from_pretrained('tencent/HY-World-2.0') |
| output = pipeline('input.png') |
| output.save('output_panorama.png') |
| ``` |
|
|
| ### Code Usage — World Generation (WorldNav, WorldStereo-2, and 3DGS) |
|
|
| The world Generation pipeline turns a panorama scene into a navigable 3D world through five stages: |
|
|
| | Stage | Script | Description | |
| |-------|--------|-------------| |
| | 1. Trajectory Planning | `traj_generate.py` | VLM-guided camera trajectory planning with obstacle-aware navigation | |
| | 2. Trajectory Rendering | `traj_render.py` | Multi-GPU point-cloud rendering along planned trajectories | |
| | 3. World Expansion | `video_gen.py` | WorldStereo-2 keyframe generation with memory-guided consistency | |
| | 4. GS Data Preparation | `gen_gs_data.py` | Extract frames, aligned depth, normals, and cameras for 3DGS training | |
| | 5. 3DGS Training | `world_gs_trainer.py` | Optimize and export the final Gaussian Splatting world | |
|
|
| For full documentation, prerequisites, and CLI arguments, see **[hyworld2/worldgen/README.md](hyworld2/worldgen/README.md)**. |
|
|
| ### Code Usage — WorldMirror 2.0 |
| WorldMirror 2.0 supports the following usage modes: |
|
|
| - [Code Usage](#code-usage--worldmirror-20) |
| - [Gradio App](#gradio-app--worldmirror-20) |
|
|
| We provide a `diffusers`-like Python API for WorldMirror 2.0. Model weights are automatically downloaded from Hugging Face on first run. |
|
|
| ```python |
| from hyworld2.worldrecon.pipeline import WorldMirrorPipeline |
| |
| pipeline = WorldMirrorPipeline.from_pretrained('tencent/HY-World-2.0') |
| result = pipeline('path/to/images') |
| ``` |
|
|
| **With Prior Injection (Camera & Depth):** |
|
|
| ```python |
| result = pipeline( |
| 'path/to/images', |
| prior_cam_path='path/to/prior_camera.json', |
| prior_depth_path='path/to/prior_depth/', |
| ) |
| ``` |
|
|
| > For the detailed structure of camera/depth priors and how to prepare them, see [Prior Preparation Guide](DOCUMENTATION.md#prior-injection). |
|
|
| **CLI:** |
|
|
| ```bash |
| # Single GPU |
| python -m hyworld2.worldrecon.pipeline --input_path path/to/images |
| |
| # Multi-GPU |
| torchrun --nproc_per_node=2 -m hyworld2.worldrecon.pipeline \ |
| --input_path path/to/images \ |
| --use_fsdp --enable_bf16 |
| ``` |
|
|
| > **Important:** In multi-GPU mode, the number of input images must be **>= the number of GPUs**. For example, with `--nproc_per_node=8`, provide at least 8 images. |
|
|
| ### Gradio App — WorldMirror 2.0 |
|
|
| We provide an interactive [Gradio](https://www.gradio.app/) web demo for WorldMirror 2.0. Upload images or videos and visualize 3DGS, point clouds, depth maps, normal maps, and camera parameters in your browser. |
|
|
| ```bash |
| # Single GPU |
| python -m hyworld2.worldrecon.gradio_app |
| |
| # Multi-GPU |
| torchrun --nproc_per_node=2 -m hyworld2.worldrecon.gradio_app \ |
| --use_fsdp --enable_bf16 |
| ``` |
|
|
| For the full list of Gradio app arguments (port, share, local checkpoints, etc.), see [DOCUMENTATION.md](DOCUMENTATION.md#gradio-app). |
|
|
|
|
|
|
| ## 🔮 Performance |
|
|
| For full benchmark results, please refer to the [technical report](https://3d-models.hunyuan.tencent.com/world/). |
|
|
| ### WorldStereo 2.0 — Camera Control |
|
|
| <table> |
| <thead> |
| <tr> |
| <th rowspan="2">Methods</th> |
| <th colspan="3" align="center">Camera Metrics</th> |
| <th colspan="4" align="center">Visual Quality</th> |
| </tr> |
| <tr> |
| <th>RotErr ↓</th><th>TransErr ↓</th><th>ATE ↓</th> |
| <th>Q-Align ↑</th><th>CLIP-IQA+ ↑</th><th>Laion-Aes ↑</th><th>CLIP-I ↑</th> |
| </tr> |
| </thead> |
| <tbody> |
| <tr><td>SEVA</td><td>1.690</td><td>1.578</td><td>2.879</td><td>3.232</td><td>0.479</td><td>4.623</td><td>77.16</td></tr> |
| <tr><td>Gen3C</td><td>0.944</td><td>1.580</td><td>2.789</td><td>3.353</td><td>0.489</td><td>4.863</td><td>82.33</td></tr> |
| <tr><td>WorldStereo</td><td>0.762</td><td>1.245</td><td>2.141</td><td>4.149</td><td><b>0.547</b></td><td>5.257</td><td>89.05</td></tr> |
| <tr><td><b>WorldStereo 2.0</b></td><td><b>0.492</b></td><td><b>0.968</b></td><td><b>1.768</b></td><td><b>4.205</b></td><td>0.544</td><td><b>5.266</b></td><td><b>89.43</b></td></tr> |
| </tbody> |
| </table> |
| |
| ### WorldStereo 2.0 — Single-View-Generated Reconstruction |
|
|
| <table> |
| <thead> |
| <tr> |
| <th rowspan="2">Methods</th> |
| <th colspan="4">Tanks-and-Temples</th> |
| <th colspan="4">MipNeRF360</th> |
| </tr> |
| <tr> |
| <th>Precision ↑</th> |
| <th>Recall ↑</th> |
| <th>F1-Score ↑</th> |
| <th>AUC ↑</th> |
| <th>Precision ↑</th> |
| <th>Recall ↑</th> |
| <th>F1-Score ↑</th> |
| <th>AUC ↑</th> |
| </tr> |
| </thead> |
| <tbody align="center"> |
| <tr> |
| <td align="left">SEVA</td> |
| <td>33.59</td> |
| <td>35.34</td> |
| <td>36.73</td> |
| <td>51.03</td> |
| <td>22.38</td> |
| <td>55.63</td> |
| <td>28.75</td> |
| <td>46.81</td> |
| </tr> |
| <tr> |
| <td align="left">Gen3C</td> |
| <td><u>46.73</u></td> |
| <td>25.51</td> |
| <td>31.24</td> |
| <td>42.44</td> |
| <td>23.28</td> |
| <td><strong>75.37</strong></td> |
| <td>35.26</td> |
| <td>52.10</td> |
| </tr> |
| <tr> |
| <td align="left">Lyra</td> |
| <td><strong>50.38</strong></td> |
| <td>28.67</td> |
| <td>32.54</td> |
| <td>43.05</td> |
| <td>30.02</td> |
| <td>58.60</td> |
| <td>36.05</td> |
| <td>49.89</td> |
| </tr> |
| <tr> |
| <td align="left">FlashWorld</td> |
| <td>26.58</td> |
| <td>20.72</td> |
| <td>22.29</td> |
| <td>30.45</td> |
| <td>35.97</td> |
| <td>53.77</td> |
| <td>42.60</td> |
| <td>53.86</td> |
| </tr> |
| <tr> |
| <td align="left">WorldStereo 2.0</td> |
| <td>43.62</td> |
| <td><u>41.02</u></td> |
| <td><u>41.43</u></td> |
| <td><u>58.19</u></td> |
| <td><strong>43.19</strong></td> |
| <td><u>65.32</u></td> |
| <td><strong>51.27</strong></td> |
| <td><strong>65.79</strong></td> |
| </tr> |
| <tr> |
| <td align="left">WorldStereo 2.0 (DMD)</td> |
| <td>40.41</td> |
| <td><strong>44.41</strong></td> |
| <td><strong>43.16</strong></td> |
| <td><strong>60.09</strong></td> |
| <td><u>42.34</u></td> |
| <td>64.83</td> |
| <td><u>50.52</u></td> |
| <td><u>65.64</u></td> |
| </tr> |
| </tbody> |
| </table> |
| |
| ### WorldMirror 2.0 — Point Map Reconstruction |
|
|
| **Point Map Reconstruction on 7-Scenes, NRGBD, and DTU.** We report the mean Accuracy and Completeness of WorldMirror under different input configurations. **Bold** results are best. "L / M / H" denote low / medium / high inference resolution. "+ all priors" denotes injection of camera extrinsics, camera intrinsics, and depth priors. |
|
|
| <table> |
| <thead> |
| <tr> |
| <th rowspan="2">Method</th> |
| <th colspan="2" align="center">7-Scenes <sub>(scene)</sub></th> |
| <th colspan="2" align="center">NRGBD <sub>(scene)</sub></th> |
| <th colspan="2" align="center">DTU <sub>(object)</sub></th> |
| </tr> |
| <tr> |
| <th>Acc. ↓</th><th>Comp. ↓</th> |
| <th>Acc. ↓</th><th>Comp. ↓</th> |
| <th>Acc. ↓</th><th>Comp. ↓</th> |
| </tr> |
| </thead> |
| <tbody> |
| <tr><td colspan="7"><em>WorldMirror 1.0</em></td></tr> |
| <tr><td> L</td><td>0.043</td><td>0.055</td><td>0.046</td><td>0.049</td><td>1.476</td><td>1.768</td></tr> |
| <tr><td> L + all priors</td><td>0.021</td><td>0.026</td><td>0.022</td><td>0.020</td><td>1.347</td><td>1.392</td></tr> |
| <tr><td> M</td><td>0.043</td><td>0.049</td><td>0.041</td><td>0.045</td><td>1.017</td><td>1.780</td></tr> |
| <tr><td> M + all priors</td><td>0.018</td><td>0.023</td><td>0.016</td><td>0.014</td><td>0.735</td><td>0.935</td></tr> |
| <tr><td> H</td><td>0.079</td><td>0.087</td><td>0.077</td><td>0.093</td><td>2.271</td><td>2.113</td></tr> |
| <tr><td> H + all priors</td><td>0.042</td><td>0.041</td><td>0.078</td><td>0.082</td><td>1.773</td><td>1.478</td></tr> |
| <tr><td colspan="7"></td></tr> |
| <tr><td colspan="7"><em>WorldMirror 2.0</em></td></tr> |
| <tr><td> L</td><td>0.041</td><td>0.052</td><td>0.047</td><td>0.058</td><td>1.352</td><td>2.009</td></tr> |
| <tr><td> L + all priors</td><td>0.019</td><td>0.024</td><td>0.017</td><td>0.015</td><td>1.100</td><td>1.201</td></tr> |
| <tr><td> M</td><td>0.033</td><td>0.046</td><td>0.039</td><td>0.047</td><td>1.005</td><td>1.892</td></tr> |
| <tr><td> M + all priors</td><td>0.013</td><td>0.017</td><td><b>0.013</b></td><td><b>0.013</b></td><td>0.690</td><td>0.876</td></tr> |
| <tr><td> H</td><td>0.037</td><td>0.040</td><td>0.046</td><td>0.053</td><td>0.845</td><td>1.904</td></tr> |
| <tr><td> <b>H + all priors</b></td><td><b>0.012</b></td><td><b>0.016</b></td><td>0.015</td><td>0.016</td><td><b>0.554</b></td><td><b>0.771</b></td></tr> |
| </tbody> |
| </table> |
| |
| ### WorldMirror 2.0 — Prior Comparison |
| |
| **Comparison with Pow3R and MapAnything under Different Prior Conditions.** Results are averaged on 7-Scenes, NRGBD, and DTU datasets. Pow3R (pro) refers to the original Pow3R with Procrustes alignment. |
|
|
|
|
| <p align="center"> |
| <img src="assets/prior_comparison2_wm2.png" width="85%"> |
| </p> |
|
|
|
|
|
|
|
|
| ## 🎬 More Examples |
|
|
| <table align="center" style="border: none;"> |
| <tr> |
| <td align="center" width="50%"><img src="assets/screenshot_3.gif" width="100%"></td> |
| <td align="center" width="50%"><img src="assets/screenshot_4.gif" width="100%"></td> |
| </tr> |
| <tr> |
| <td align="center" width="50%"><img src="assets/screenshot_5.gif" width="100%"></td> |
| <td align="center" width="50%"><img src="assets/screenshot_6.gif" width="100%"></td> |
| </tr> |
| <tr> |
| <td align="center" width="50%"><img src="assets/screenshot_9.gif" width="100%"></td> |
| <td align="center" width="50%"><img src="assets/screenshot_10.gif" width="100%"></td> |
| </tr> |
| </table> |
| |
|
|
| ## 📖 Documentation |
|
|
| For detailed usage guides, parameter references, output format specifications, and prior injection instructions, see **[DOCUMENTATION.md](DOCUMENTATION.md)**. |
|
|
|
|
| ## 📚 Citation |
|
|
| If you find HunyuanWorld 2.0 useful for your research, please cite: |
|
|
| ```bibtex |
| @article{hyworld22026, |
| title={HY-World 2.0: A Multi-Modal World Model for Reconstructing, Generating, and Simulating 3D Worlds}, |
| author={Team HY-World}, |
| journal={arXiv preprint arXiv:2604.14268}, |
| year={2026} |
| } |
| |
| @article{hunyuanworld2025tencent, |
| title={HunyuanWorld 1.0: Generating Immersive, Explorable, and Interactive 3D Worlds from Words or Pixels}, |
| author={Team HunyuanWorld}, |
| year={2025}, |
| journal={arXiv preprint} |
| } |
| ``` |
|
|
| ## 📧 Contact |
|
|
| Please send emails to tengfeiwang12@gmail.com for questions or feedback. |
|
|
|
|
| ## 🙏 Acknowledgements |
|
|
| We would like to thank [HunyuanWorld 1.0](https://github.com/Tencent-Hunyuan/HunyuanWorld-1.0), [WorldMirror](https://github.com/Tencent-Hunyuan/HunyuanWorld-Mirror), [WorldPlay](https://github.com/Tencent-Hunyuan/HY-WorldPlay), [WorldStereo](https://github.com/FuchengSu/WorldStereo), [HunyuanImage](https://github.com/Tencent-Hunyuan/HunyuanImage-3.0) for their great work. |
