Update README.md

README.md

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 ---
 license: cc-by-sa-4.0
+language:
+- en
+base_model:
+- tencent/HunyuanCustom
 ---
+<div align="center">
+
+<h1 align="center">
+  CustomX: Unified Character, Action, and Scene Customization in Video World Models
+</h1>
+
+<h3 align="center">
+  ECCV 2026
+</h3>
+
+<p align="center">
+  <a href="https://arxiv.org/abs/2512.17796"><img src="https://img.shields.io/badge/arXiv-Paper-B31B1B?style=flat&labelColor=555555&logo=arxiv&logoColor=white" alt="arXiv"></a>
+  <a href="https://snowflakewang.github.io/CustomX_Page/"><img src="https://img.shields.io/badge/Project-Page-4F46E5?style=flat&labelColor=555555&logo=googlechrome&logoColor=white" alt="Project Page"></a>
+  <a href="https://github.com/snowflakewang/CustomX"><img src="https://img.shields.io/badge/Code-GitHub-181717?style=flat&labelColor=555555&logo=github&logoColor=white" alt="Code"></a>
+</p>
+
+</div>
+
+---
+
+## 📖 Abstract
+
+Recent advances in world models have greatly enhanced interactive environment simulation. Existing methods mainly fall into two categories: (1) static world generation models, which construct 3D environments without active agents, and (2) controllable-entity models, which allow a single entity to perform limited actions in an otherwise uncontrollable environment. In this work, we introduce CustomX, leveraging the realism and structural grounding of static world generation while extending controllable-entity models to support user-specified characters capable of performing open-ended actions. Users can provide a 3DGS scene and a character, then use natural language to direct the character to perform diverse behaviors, ranging from basic locomotion to object-centric interactions, while freely exploring the environment. CustomX synthesizes temporally coherent video clips that preserve visual fidelity with the provided scene and character, formulated as a conditional autoregressive video generation problem. Built upon a pre-trained video generator, our training strategy significantly enhances motion dynamics while maintaining generalization across actions and characters. Our evaluation covers a broad range of aspects, including visual quality, character consistency, action controllability, and long-horizon coherence.
+
+<div align="center">
+  <img src="./assets/teaser_v3.jpg" width="100%" alt="CustomX Teaser"/>
+</div>
+
+## 🛠️ Installation
+```bash
+conda create -n customx python==3.11.9
+conda activate customx
+
+pip install uv
+
+uv pip install torch==2.4.0 torchvision==0.19.0 torchaudio==2.4.0 --index-url https://download.pytorch.org/whl/cu124
+uv pip install -r requirements.txt
+
+wget https://github.com/Dao-AILab/flash-attention/releases/download/v2.6.3/flash_attn-2.6.3+cu123torch2.4cxx11abiFALSE-cp311-cp311-linux_x86_64.whl
+uv pip install flash_attn-2.6.3+cu123torch2.4cxx11abiFALSE-cp311-cp311-linux_x86_64.whl
+```
+
+## 📦 Download Checkpoints
+### HunyuanCustom Base Model
+Download HunyuanCustom base model [here](https://huggingface.co/tencent/HunyuanCustom).
+
+Only need to download the following files from HunyuanCustom:
+```shell
+CustomX
+└── models
+    └── base
+        ├── hunyuancustom_editing_720P
+        │   └── mp_rank_00_model_states.pt
+        ├── vae_3d
+        ├── openai_clip-vit-large-patch14
+        └── llava-llama-3-8b-v1_1
+```
+
+### CustomX LoRA
+```bash
+TOKEN=xxx # add your Hugging Face token here
+
+hf download --token $TOKEN \
+    SnowflakeWang/CustomX \
+    --local-dir models/lora
+```
+
+## 🚀 Inference
+
+### Input Preparation
+We provide a sample input in the [input](input) directory. To use your own inputs, organize them following the same structure.
+
+```shell
+input
+├── character_assets
+│   └── orangeRobot
+│       ├── input_list
+│       │   ├── ar_cond.list
+│       │   ├── character.list
+│       │   ├── output_video.list
+│       │   ├── pos_prompt.list
+│       │   ├── scene.list
+│       │   └── scene_mask.list
+│       └── multi_view
+│           ├── 000_0001.png
+│           ├── 002_0001.png
+│           ├── 004_0001.png
+│           └── 006_0001.png
+└── scene_assets
+    └── futureUtopia
+        ├── all_frame_mask.mp4
+        └── videos
+            ├── 0.mp4
+            ├── 1.mp4
+            └── ...
+```
+
+### Multi-GPU Inference (Recommended)
+```bash
+# 720P video inference
+# Tested on 8 NVIDIA A100-80G GPUs
+bash inference_multi_gpu.sh
+```
+
+### Single-GPU Inference
+```bash
+# 360P video inference
+# Tested on 1 NVIDIA A100-80G GPU
+bash inference_single_gpu.sh
+```
+
+### Video Merging
+```bash
+# Merge videos generated by auto-regressive inference
+python video_merge.py --input_dir "output/orangeRobot_futureUtopia"
+```
+
+## 🔮 Citation
+
+```bibtex
+@misc{wang2026customx,
+      title={CustomX: Unified Character, Action, and Scene Customization in Video World Models}, 
+      author={Yitong Wang and Fangyun Wei and Hongyang Zhang and Bo Dai and Yan Lu},
+      year={2026},
+      eprint={2512.17796},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2512.17796}, 
+}
+```
+
+## 💐 Acknowledgements
+
+- [HunyuanCustom](https://github.com/Tencent-Hunyuan/HunyuanCustom)
+- [Diffusers](https://github.com/huggingface/diffusers)
+- [Transformers](https://github.com/huggingface/transformers)
+- [DeepSpeed](https://github.com/deepspeedai/DeepSpeed)
+- [Grand Theft Auto V](https://www.rockstargames.com/gta-v)
+
+## 📄 License
+
+This project is licensed under the [CC BY-SA 4.0 License](http://creativecommons.org/licenses/by-sa/4.0/).