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README.md

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+<h1 align="center">
+  <span style="color:#2196f3;"><b>MiniMax</b></span><span style="color:#f06292;"><b>-Remover</b></span>: Taming Bad Noise Helps Video Object Removal
+</h1>
+
+<p align="center">
+  Bojia Zi<sup>*</sup>,
+  Weixuan Peng<sup>*</sup>,
+  Xianbiao Qi<sup>†</sup>,
+  Jianan Wang, Shihao Zhao, Rong Xiao, Kam-Fai Wong<br>
+  <sup>*</sup> Equal contribution. <sup>†</sup> Corresponding author.
+</p>
+
+<p align="center">
+  <a href="https://huggingface.co/zibojia/minimax-remover"><img alt="Huggingface Model" src="https://img.shields.io/badge/%F0%9F%A4%97%20Huggingface-Model-brightgreen"></a>
+  <a href="https://github.com/zibojia/MiniMax-Remover"><img alt="Github" src="https://img.shields.io/badge/MiniMaxRemover-github-black"></a>
+  <a href="https://huggingface.co/spaces/zibojia/MiniMaxRemover"><img alt="Huggingface Space" src="https://img.shields.io/badge/%F0%9F%A4%97%20Huggingface-Space-1e90ff"></a>
+  <a href="https://arxiv.org/abs/2505.24873"><img alt="arXiv" src="https://img.shields.io/badge/MiniMaxRemover-arXiv-b31b1b"></a>
+  <a href="https://www.youtube.com/watch?v=KaU5yNl6CTc"><img alt="YouTube" src="https://img.shields.io/badge/Youtube-video-ff0000"></a>
+  <a href="https://minimax-remover.github.io"><img alt="Demo Page" src="https://img.shields.io/badge/Website-Demo%20Page-yellow"></a>
+</p>
+
+---
+
+## 🚀 Overview
+
+**MiniMax-Remover** is a fast and effective video object remover based on minimax optimization. It operates in two stages: the first stage trains a remover using a simplified DiT architecture, while the second stage distills a robust remover with CFG removal and fewer inference steps.
+
+---
+
+## ✨ Features: 
+
+* **Fast:** Requires only 6 inference steps and does not use CFG, making it highly efficient.
+
+* **Effective:** Seamlessly removes objects from videos and generates high-quality visual content.
+
+* **Robust:** Maintains robustness by preventing the regeneration of undesired objects or artifacts within the masked region, even under varying noise conditions.
+
+---
+
+## 🛠️ Installation
+
+All dependencies are listed in `requirements.txt`.
+
+```bash
+pip install -r requirements.txt
+```
+
 ---
-title: MiniMax Remover
-emoji: ⚡
-colorFrom: purple
-colorTo: red
-sdk: gradio
-sdk_version: 5.34.1
-app_file: app.py
-pinned: false
-license: cc-by-nc-2.0
-short_description: MiniMax-Remover is a fast and effective video object remover
+
+## 🏃‍♂️ Gradio Demo
+
+<p align="center">
+  <a href="https://youtu.be/1V7Ov4vmnBc" target="_blank">
+    <img src="./imgs/gradio_demo.gif" alt="firstpage" style="width:80%;" />
+  </a>
+</p>
+
+You can use this gradio demo to remove objects. Note that you don't need to compile the sam2.
+```bash
+cd gradio_demo
+python3 test.py
+```
+
+---
+
+## 📂 Download
+
+```shell
+huggingface-cli download zibojia/minimax-remover --include vae transformer scheduler --local-dir .
+```
+
+---
+
+## ⚡ Quick Start
+
+### Minimal Example
+
+```python
+import torch
+from diffusers.utils import export_to_video
+from decord import VideoReader
+from diffusers.models import AutoencoderKLWan
+from transformer_minimax_remover import Transformer3DModel
+from diffusers.schedulers import UniPCMultistepScheduler
+from pipeline_minimax_remover import Minimax_Remover_Pipeline
+
+random_seed = 42
+video_length = 81
+device = torch.device("cuda:0")
+
+# Load model weights separately
+vae = AutoencoderKLWan.from_pretrained("./vae", torch_dtype=torch.float16)
+transformer = Transformer3DModel.from_pretrained("./transformer", torch_dtype=torch.float16)
+scheduler = UniPCMultistepScheduler.from_pretrained("./scheduler")
+
+images = # images in range [-1, 1]
+masks = # masks in range [0, 1]
+
+# Initialize the pipeline (pass the loaded weights as objects)
+pipe = Minimax_Remover_Pipeline(vae=vae, transformer=transformer, \
+    scheduler=scheduler, torch_dtype=torch.float16
+).to(device)
+
+result = pipe(images=images, masks=masks, num_frames=video_length, height=480, width=832, \
+    num_inference_steps=12, generator=torch.Generator(device=device).manual_seed(random_seed), iterations=6 \
+).frames[0]
+export_to_video(result, "./output.mp4")
+```
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+## 📧 Contact
+
+Feel free to send an email to [[email protected]](mailto:[email protected]) if you have any questions or suggestions.