---
license: apache-2.0
base_model:
- black-forest-labs/FLUX.1-dev
tags:
- image2image
- layer-decomposition
---
<div align="center">

<div align="center">
  <img src="./assets/logo.png" alt="RevealLayer Logo" height="96">
</div>

<h2 align="center">
  Disentangling Hidden and Visible Layers via Occlusion-Aware Image Decomposition
</h2>

<div>
  <strong>
  Binhao Wang<sup>1,2,*</sup>, 
  Shihao Zhao<sup>1,2,*</sup>, 
  Bo Cheng<sup>2,*,†</sup>, 
  Qiuyu Ji<sup>1,2</sup>, 
  Yuhang Ma<sup>2</sup>,<br>
  Liebucha Wu<sup>2</sup>, 
  Shanyuan Liu<sup>2</sup>, 
  Dawei Leng<sup>2,‡</sup>, 
  Yuhui Yin<sup>2</sup>
  </strong>
</div>

<div>
  <sup>1</sup>Wenzhou University   
  <sup>2</sup>360 AI Research
</div>

<div>
  <sup>*</sup> Equal Contribution.  
  <sup>†</sup> Project Lead.  
  <sup>‡</sup> Corresponding Author.
</div>

<br>

<div>
  <h3>🔥 Accepted by ICML 2026!</h3>
</div>

<div>
  <a href="https://github.com/360CVGroup/RevealLayer/" target="_blank">
    <img src="https://img.shields.io/static/v1?label=Project%20Page&message=Github&color=blue&logo=github-pages">
  </a>
   
  <a href="https://arxiv.org/abs/2605.11818" target="_blank">
    <img src="https://img.shields.io/static/v1?label=Paper&message=arXiv&color=red&logo=arxiv">
  </a>
   
  <a href="https://huggingface.co/qihoo360/RevealLayer" target="_blank">
    <img src="https://img.shields.io/static/v1?label=Dataset&message=RevealLayer&color=green">
  </a>
   
  <a href="https://huggingface.co/qihoo360/RevealLayer" target="_blank">
    <img src="https://img.shields.io/static/v1?label=Model&message=HuggingFace&color=yellow">
  </a>
</div>

<br>

<strong>
RevealLayer decomposes an RGB image into multiple RGBA layers, enabling precise layer separation and reliable recovery of occluded content in natural scenes.
</strong>

<br><br>

<div style="width: 100%; text-align: center; margin: auto;">
    <img style="width:100%" src="assets/demo1.png" alt="RevealLayer teaser">
</div>

For more visual results, go checkout our <a href="https://360cvgroup.github.io/RevealLayer/" target="_blank">project page</a>.

---

</div>

## ⭐ Update

- **[2026.05]** RevealLayer has been accepted by ICML 2026.
- **[2026.05]** We released the RevealLayer paper and inference code.
- **[2026.05]** We released the RevealLayer checkpoint on [Hugging Face](https://huggingface.co/qihoo360/RevealLayer).

### ✅ TODO

- [ ] Release RevealLayer-100K and RevealLayerBench.
- [ ] Release an improved version of RevealLayer with stronger layer consistency and higher inference efficiency.

---

## 🎃 Overview

RevealLayer focuses on occlusion-aware image layer decomposition, recovering visible and hidden RGBA layers from a single RGB image with region guidance.

<div style="width: 100%; text-align: center; margin: auto;">
    <img style="width:100%" src="assets/framework.png" alt="RevealLayer framework">
</div>

---

## 📷 Datasets

<div style="width: 100%; text-align: center; margin: auto;">
    <img style="width:100%" src="assets/pipeline.png" alt="RevealLayer dataset pipeline">
</div>

We construct a large-scale multi-layer image decomposition dataset, including **RevealLayer-100K** for training and **RevealLayerBench** for evaluation. RevealLayer-100K contains 100K multi-layer natural image tuples with RGB images, background layers, RGBA foreground layers, and bounding boxes. RevealLayerBench contains 200 high-quality manually curated images, covering challenging cases such as complex occlusions, large-area objects, transparent materials, small foreground objects, and multi-layer scenes.

🔥 We will release **RevealLayer-100K** and **RevealLayerBench** on [Hugging Face](https://huggingface.co/qihoo360/RevealLayer). We hope they can serve as useful training and evaluation resources for future research on occlusion-aware image layer decomposition.

> 🚩 The datasets are intended for research use. Please follow the license and terms provided with the released dataset.


---

## 📑 Citation

If you find our work useful for your research, please consider citing:

```bibtex
@inproceedings{wang2026reveallayer,
  title={RevealLayer: Disentangling Hidden and Visible Layers via Occlusion-Aware Image Decomposition},
  author={Wang, Binhao and Zhao, Shihao and Cheng, Bo and Ji, Qiuyu and Ma, Yuhang and Wu, Liebucha and Liu, Shanyuan and Leng, Dawei and Yin, Yuhui},
  booktitle={International Conference on Machine Learning},
  year={2026}
}
```

---

## 📝 License

This project is licensed under the [Apache License 2.0](LICENSE).