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| license: apache-2.0 | |
| # Video-Coder 9B Model | |
| This repository contains the Video-Coder-9B for [Video-Coder: Reinforcing Agentic Coding for Video Generation](). | |
| [**π Project Page**]() | [**π Paper**]() | [**π» Code**]() | |
| # π Intro | |
| <div align="center"> | |
| <img src="https://raw.githubusercontent.com/CYWang735/Video-Coder/main/assets/teaser.png" alt="Video-Coder Overview" width="80%"> | |
| </div> | |
| We introduce **Video-Coder**, the first attempt to train a **code-driven video generation agent**, which autonomously | |
| writes and executes code to **construct a dynamic 3D scene (Draft Video)** that provides structure and | |
| motion signals to downstream video generators. | |
| We curate two high-quality datasets, **Video-Coder-SFT-10k** and **Video-Coder-RL-4k**, | |
| which contain diverse prompts and ground-truth reference videos. | |
| We further develop the **Video-Coder Harness**, a unified interactive environment integrating code execution, 3D scene rendering, | |
| and execution feedback for agent training and inference. | |
| Video-Coder achieves significant gains, | |
| improving Minimax-H3 by **approximately 7 points on PhyGenBench and 24 points on VBench-2.0**. | |
| ## π₯ Demo | |
| <div align="center"> | |
| <img src="https://raw.githubusercontent.com/CYWang735/Video-Coder/main/assets/qualitative.png" alt="Inference Process" width="85%"> | |
| </div> | |
| ## π Training and Inference | |
| For detailed instructions on setup, SFT/RL training, and inference, please refer to the [official GitHub repository](https://github.com/CYWang735/Video-Coder). | |
| ## Citation | |
| If you find this work helpful for your research, please consider citing: | |
| ```bibtex | |
| ``` |