Create README.md

README.md

@@ -0,0 +1,100 @@
+---
+annotations_creators:
+- expert-generated
+language:
+- en
+license: mit
+task_categories:
+- text-to-3d
+- text-to-video
+- other
+tags:
+- blender
+- procedural-generation
+- physics-simulation
+- 4d-generation
+- code-generation
+pretty_name: Code4D Benchmark
+size_categories:
+- n<1K
+---
+
+# Dataset Card for Code4D (Code2Worlds)
+
+## Dataset Description
+
+- **Paper:** [Code2Worlds: Empowering Coding LLMs for 4D World Generation](https://arxiv.org/abs/2602.11757)
+- **Repository:** [GitHub](https://github.com/AIGeeksGroup/Code2Worlds)
+
+### Dataset Summary
+
+The **Code4D** benchmark is a dataset designed to evaluate the capability of Large Language Models (LLMs) in generating physically grounded 4D environments. It pairs natural language prompts with complex 3D scenes (provided here as `.blend` files) that exhibit temporal evolution, physical interactions, and atmospheric changes.
+
+Unlike existing text-to-3D datasets that focus solely on static structures, Code4D challenges models on dynamic fidelity, including fluid dynamics, particle systems, rigid-body dynamics, and soft-body simulations.
+
+This dataset supports the **Code2Worlds** framework, which formulates 4D generation as language-to-simulation code generation using a dual-stream architecture (Object Stream and Scene Stream).
+
+### Supported Tasks and Leaderboards
+
+- **Text-to-4D Scene Generation:** Generating dynamic 3D scenes from text descriptions.
+- **Procedural Code Generation:** Evaluating LLMs on generating Blender/Infinigen API calls.
+- **Physics Simulation Benchmarking:** Assessing the realism of generated physical interactions.
+
+### Languages
+
+The prompts and documentation are in **English**.
+
+---
+
+## Dataset Structure
+
+### Data Instances
+
+Each instance in the dataset consists of a text prompt and its corresponding Blender project file (`.blend`).
+
+**Example:**
+
+* **Prompt:** "A breeze stirs through the autumn forest, gently swaying the entire tree as leaves dance in the wind."
+* **File:** `scene_1.blend`
+
+### Data Fields
+
+- `prompt` (string): The natural language instruction describing the scene and desired dynamics.
+- `blend_file` (file): The Blender 3D project file containing the scene layout, assets, and simulation settings.
+---
+
+## Dataset Creation
+
+### Curation Rationale
+
+The dataset was constructed to address the "semantic-physical execution gap" in generative models. It specifically targets scenarios where monolithic generation fails, requiring precise control over both local object structures and global environmental layouts.
+
+---
+
+## Considerations for Using the Data
+
+### Software Dependencies
+
+To open and render the `.blend` files properly, you need:
+- **Blender 4.3** or higher.
+- **Infinigen** libraries.
+
+### Computational Requirements
+
+The benchmark scenes are designed for high-fidelity rendering.
+- **Nature Scenes:** Configured for 1920x1080 resolution, 240 frames, 128 samples.
+- **Indoor Scenes:** Configured for 1920x1080 resolution, 120 frames, 196 samples.
+
+---
+
+## Citation
+
+If you use this dataset in your research, please cite the following paper:
+
+```bibtex
+@article{zhang2026code2worlds,
+  title={Code2Worlds: Empowering Coding LLMs for 4D World Generation},
+  author={Zhang, Yi and Wang, Yunshuang and Zhang, Zeyu and Tang, Hao},
+  journal={arXiv preprint arXiv:2602.11757},
+  year={2026}
+}